List of reference targets (countryspecific

Transcription

1 WP4: D4.2 List of reference targets (countryspecific & EU-wide) for grid integration of DER This project has received funding from the European Union s Seventh Framework Programme for research, technological development and demonstration under grant agreement no

2 WP4: D4.2 ID & Title : D4.2 List of reference targets (country-specific & EU-wide) for Number of pages : 79 grid integration of DER Short Description (Max. 50 words): This document presents the solutions selected using results and experience gained from the IGREENGrid demonstration projects, including a quantitative evaluation using KPIs and a qualitative evaluation to assess the feasibility for large scale deployment on a European scale. A reduced list of solutions are presented with recommendations for further study. Version Date Modifications nature Author V0.3 18/12/2015 Accessibility: PU, Public Changes over document content and contributions integration PP, Restricted to other program participants (including the Commission Services) Gareth Bissell RE, Restricted to other a group specified by the consortium (including the Commission Services) CO, Confidential, only for members of the consortium (including the Commission Services) If restricted, please specify here the group: Owner / Main responsible: ENEL Reviewed by: RSE V /12/18 2/79

3 WP4: D4.2 Authors Version Date Modifications nature Author name (s) Company V /06/17 Initialization V /11/17 Document content V /12/4 V /12/18 Changes over document content and contributions integration Changes over document content and contributions integration G. Bissell M. Rossi N. Ruiz J. Varela/D. Rubio G. Bissell M. Rossi N. Ruiz/J. Oyarzabal D. Rubio/J. Varela M. Sebastián-Viana E. Álvarez/F. Salazar C. Calpe/J. Reidick/M. Storp R. Priewasser A. Abart/E. Traxler M. Kouveletsou B. Benoit A. Dimeas / D. Koukoula/ E. Karfopoulos G. Bissell N. Ruiz D. Rubio/J. Varela M. Sebastián-Viana C. Calpe/J. Reidick/M. Storp G. Bissell N. Ruiz M. Sebastián-Viana E. Álvarez/F. Salazar ENEL RSE TECNALIA, IBERDROLA ENEL RSE TECNALIA IBERDROLA ERDF GNF RWE SAG EAG HEDNO AIT ICCS-NTUA ENEL TECNALIA IBERDROLA ERDF RWE ENEL TECNALIA ERDF GNF V /12/18 3/79

4 WP4: D4.2 Abstract This document focuses on the selection of solutions from the IGREENGrid demonstration projects for further evaluation, using simulation studies in Work Package 5. The analysis was based on a qualitative evaluation using the experiences and results from the demonstration projects. Reference is also given to the results from the IGREENGrid KPIs that were calculated within Work Package 4. A list of selected solutions is provided along with a first overview of their potential for Scalability and Replicability (S&R) and recommendations for simulation studies in Work Package 5. Reference targets (country-specific & EU-wide) for grid integration of DER were considered based on the IGREENGrid KPIs. V /12/18 4/79

5 WP4: D4.2 Table of contents AUTHORS... 3 ABSTRACT... 4 TABLE OF CONTENTS... 5 LIST OF FIGURES & TABLES INTRODUCTION AND SCOPE OF THE DOCUMENT OBJECTIVE AND APPROACH PRELIMINARY EVALUATION Methodology Results Conclusions List of solutions for Detailed evaluation DETAILED EVALUATION Qualitative evaluation Methodology Performance Social Aspects Scalability and Replicability Reliability Risk on Investment Technical Complexity Technical Requirements Regulatory and Market Requirements Economical Requirements Results Conclusions Quantitative Evaluation using KPIs KPIIGG.1 Increase of DRES Hosting Capacity KPIIGG.2 Improvement of Quality of Supply KPIIGG.3 Increase of Energy Efficiency KPIs results conclusions and targets MOST PROMISING SOLUTIONS SCALABILITY AND REPLICABILITY ANALYSIS (SRA) V /12/18 5/79

6 WP4: D Methodology Overview of the methodology S&R Scenarios S&R Parameters General concepts and conventions Outputs of the SRA Results Conclusions MV Voltage Monitoring Solutions LV Voltage Monitoring Solutions MV Voltage Control Solutions LV Voltage Control Solutions MV Congestion Management Solutions RECOMMENDATIONS FOR SIMULATION STUDIES AND REFERENCE TARGETS CONCLUSIONS ANNEXES REFERENCES Project Documents External documents V /12/18 6/79

7 WP4: D4.2 List of figures & tables Figure 1 Process diagram for Work Package Figure 2 Two-stage evaluation process for selecting solutions from demonstration projects Figure 3 Preliminary Evaluation Process Figure 4 Voltage profile along feeder example Figure 5 Overview of voltage control solutions Figure 1: S&R Scenarios Figure 7 Overall assessment matrix Figure 8 Sample overall assessment graphic Figure 9 Multi-criteria evaluation of MV Voltage Monitoring implementations (Average values) Figure 10 Multi-criteria evaluation of LV Voltage Monitoring implementations (Average values) Figure 11 Multi-criteria evaluation of MV Voltage Control implementations (Average values) Figure 12 Multi-criteria evaluation of LV Voltage Control implementations (Average values) Figure 13 Multi-criteria evaluation of MV Congestion Management implementations (Average values) Table 1 (Acronyms) Table 2 Preliminary evaluation deployment potential criteria Table 3 Preliminary evaluation deployment potential results Table 4 Prioritisation by solution category from Preliminary Evaluation results Table 5 Categories of capital and operational costs considered for qualitative evaluation of economic requirements for each solution Table 6 Deployment potential using aggregated scores from qualitative evaluation Table 7 Average deployment potential by 'Functionality' category sorted from high to low Table 8 Increase of DRES hosting capacity experienced in IGREENGrid DEMO projects (MV solutions) Table 9 Increase of DRES hosting capacity experienced in IGREENGrid DEMO projects (LV solutions) Table 10 Improvement of Quality of Supply experienced in IGREENGrid DEMO projects (MV solutions) Table 11 Increase of energy efficiency experienced in IGREENGrid DEMO projects (MV solutions) Table 12 Increase of energy efficiency experienced in IGREENGrid DEMO projects (LV solutions) V /12/18 7/79

8 WP4: D4.2 Table 13 Targets of DRES Hosting Capacity Increase for MV solutions Table 14 Targets of DRES Hosting Capacity Increase for LV solutions Table 15 Results from Qualitative evaluation and DSO survey Table 16 S&R scenarios overview Table 17 Parameters assessment criteria V /12/18 8/79

9 WP4: D4.2 1 Introduction and scope of the document This deliverable summarises the approach, results and conclusions for the work that was completed in Work Package 4. The IGREENGrid project comprises of eight DSO partners and uses experience gained from large scale demonstration projects for the deployment of novel solutions to address DG integration. The main objectives of this Work Package are to identify what could be considered as the most promising of these solutions. It was specified within the scope of Work Package 4 that solutions should be based on the performance results from the IGREENGrid KPIs, as defined in Work Package 2, and a qualitative evaluation that would consider all aspects that would impact the feasibility of deployment on a national and European scale. It was necessary to calculate the IGREENGrid KPIs within Work Package 4. This is an addition to what was within the scope of this work package. The KPI calculation methodology and IGREENGrid KPI results are also presented within this deliverable. A scalability and replicability evaluation was completed for the most promising solutions and recommendations were made for further study, using computer based modelling and simulation studies in Work Package 5. It is also an objective of Work Package 4 to identify what targets should be reached from the simulation studies to reach a best-case scenario. These would include the IGREENGrid KPIs where possible and other targets not related to the KPIs. V /12/18 9/79

10 WP4: D4.2 Notations, abbreviations and acronyms AD AMI AVR BaU CBA DG DSE DMS DRES DSM DSO EC HV IT KPI LV LTE MV OLTC OPF PCC PLF PV QoS RTU SCADA SE SRA SG SGAM S&R StatCom Active Demand Advanced Metering Infrastructure Automatic Voltage Regulator Business as Usual Cost Benefit Analysis Distributed Generator Distribution State Estimator Distribution Management System Distributed Renewable Energy Sources Demand Side Management Distribution System Operator European Commission High Voltage Information Technologies Key Performance Indicator Low Voltage Long-Term Evolution Medium Voltage On Load Tap Changer Optimal Power Flow Point of Common Coupling Probabilistic Load Flow Photovoltaic Quality of Service Remote Terminal Unit Supervisory Control and Data Acquisition State Estimation Scalability and Replicability Analysis Smart Grid Smart Grid Architecture Model Scalability & Replicability Static Compensator V /12/18 10/79

11 WP4: D4.2 SUT TSO WP Solution Under Test Transmission System Operator Work Package Table 1 (Acronyms) V /12/18 11/79

12 WP4: D4.2 2 Objective and approach Within the six demonstration projects that are being considered by the IGREENGrid project, a range of solutions for DG integration, using novel technologies are being tested. These are described in Work Package 2 and Work Package 3 in deliverables D2.1 and D3.1. The objective of Work Package 4 is to select a reduced list of solutions from these demonstration projects with recommendations and targets for simulation studies that will further evaluate the deployment potential of these solutions within networks throughout Europe. Using the results and experiences from the IGREENGrid demonstration projects, the most promising solutions were selected using qualitative assessment and performance results from the demonstration projects. Finally a scalability and replicability analysis was completed for the reduced list of solutions, selected for further study. Recommendations and performance targets were also proposed for the simulation studies. The simulation studies will be completed in the next step of the IGREENGrid project under Work Package 5. The overall process for Work Package 4 is illustrated in the diagram below. SELECT Preliminay evaluation Detailed evaluation REVIEW Scalability and Replicability Analysis RECOMMEND Recomendations for further study Identification of performance targets Figure 1 Process diagram for Work Package 4 As illustrated in Figure 2, the selection of solutions from the demonstration projects was based on a two-stage evaluation process. A preliminary evaluation was used as a first step to filter the solutions based on relevance to DG integration on a European scale, deployment feasibility and expected economic benefits. Based on the experience gained throughout the IGREENGrid project, a qualitative approach was used for the first step as this was considered to be the best way to identify which solutions are most likely to be successful for large scale deployment addressing DG integration. The Preliminary evaluation was used to produce a reduced list of solutions that were then studied in more detail. The Detailed evaluation consists of a qualitative evaluation based on the expectations of the experts from the demonstration projects and identified key factors that would V /12/18 12/79

13 WP4: D4.2 influence the deployment feasibility, performance, both technical and economic and the effectiveness of the solutions in addressing DG integration. The outcome of this evaluation was then validated using the performance results from the demonstration projects provided by the calculated IGREENGrid KPIs.. Preliminary evaluation Pre-filter of solutions based on alignment with EEGI objectives, availability of information and data and prioritisation fo the solutions to be studied Detailed evaluation Evaluation based on KPI results and other key factors that will influence the successful deployment and effectiveness of the solutions outside the demo project using a quantitative and qualitative evaluation process. Figure 2 Two-stage evaluation process for selecting solutions from demonstration projects The outcome of this work will produce a list of solutions from the demonstration projects to be investigated further using simulation studies to evaluate their deployment potential and benefits towards DRES integration. These recommendations are based on the experience of the demonstration projects, the knowledge gained about the characteristics of different networks, the different approaches used by different network operators, boundary conditions and future expectations of the demands on the networks at national level. The recommendations will include a list of solutions, on which networks they should be simulated and any other factors that should be considered. An effort was also made to provide reference targets, or best case expectations for what KPIs could be achieved from the deployment of solutions across Europe. V /12/18 13/79

14 WP4: D4.2 3 Preliminary evaluation The purpose of this first stage of evaluation was to filter out any solutions that should not (based on alignment with EEGI objectives) or cannot (based on ability to provide information to model in WP5) be considered for further study in WP5. It will identify any problems regarding the potential to model and simulate these solutions. A reduced list of solutions was then determined by consideration of the expected costs, benefits in terms of integrating DG and deployment risk or risk on investment. 3.1 Methodology The preliminary evaluation will provide a simple first pass assessment that will: 1) Filter the Use Cases that should not be considered further due to the fact that they are: a) Not compliant with the objectives of the EEGI defined in the EEGI Roadmap (since all the demos are EEGI labelled projects this should not be the case). This step should therefore be considered more as a communication to the commission that we are aligned to the EEGI in terms of the objectives that are being addressed in the solutions / Use Cases that we will study. b) Not able to provide sufficient information / data to be studied further in WP5. 2) The preliminary evaluation will also prioritize the Use Cases based on those that are addressing what are considered to be the most wide spread challenges facing the distribution networks for the integration of RES. It will also consider which solutions are most feasible in terms of technical, regulatory and economic practicability. Finally it will also consider which solutions, from the demonstration projects have results to support expected benefits. The evaluation will be completed using the experience and expectations of IGREENGrid DSO partners. An overview of the Preliminary Evaluation process 1 is illustrated in Figure 3 below. Step 1 Step 2 Step 3 Is it in scope? - evaluates compliance with EEGI Objectives Can we model it? - availability of information to model solution Deployment potential - relevance, feasibility and risk Figure 3 Preliminary Evaluation Process 1 While the content and criteria remains unchanged, the structure has been improved since it was first presented in the review meeting in September V /12/18 14/79

15 WP4: D4.2 The three step process is as follows: Step 1 (Is it in scope?) Filter out Use Cases that are not addressing the EEGI Functional Objectives defined in the EEGI Roadmap [1]. Since all the demo projects have an EEGI label it can be assumed that all the Use Cases are compliant to the EEGI objectives and no further analysis will be required for this step. Step 2 (Can we model it?) This will filter out solutions that although might be considered as promising in terms of their results or potential at being deployed on a European scale, cannot be considered any further within the IGREENGrid project due to constraints on the availability of information and data that is needed to model these solutions within WP5. This step will be completed by asking the demo projects if they can provide sufficient information and data to the IGREENGrid project. The information and data requirements will be defined by WP5 based on their needs for creating a model. Since it is not possible to create a generic requirement for modelling all the solutions that are being tested within the IGREENGrid project, the requirements will be produced by category of solution based on the IGREENGrid common Use Cases. Step 3 (Deployment potential) The deployment potential will be evaluated by considering expectations on relevance to DG integration for networks across Europe, technical, economic and regulatory feasibility and risks associated with a large scale deployment. Information was gathered using the knowledge and experience from the demonstration projects. This was achieved using a survey questionnaire (See Annex A in WP4 D4.2 Annex document) and interviews with experts from each of the IGREENGrid demonstration projects. The categories of solutions are selected based on the allocation of scores and feedback received based on the following criteria: V /12/18 15/79

16 WP4: D4.2 Deployment potential 1. Extent of problem being addressed by solution on networks across Europe 2. Level of investment and operational costs associated with the solution in the demonstration project 3. Expected economical benefits of the solution (not restricted to the demo project) 4. Extent to which the expected benefits are supported by results (IGREENGrid demo or others) 5. Expected level of risk on investment for large scale deployment (on a European scale) High Medium Low High Medium Low Problem that is being addressed by the solution in demo is expected to be wide spread throughout Europe and would require substantial investment in network reinforcements (e.g. A high percentage of investment for next 10 years) Problems have been identified for certain parts of the network but relative investment needed to address these problems is medium to low (e.g. A reasonable percentage of investment for next 10 years) Similar problems on network are possible but not yet identified or are present on a small scale (e.g. A low percentage of investment for next 10 years) Low Medium High Relatively low cost compared to reinforcing the network (less than upgrading switch gear / protection system) Equivalent to moderate reinforcement costs (Upgrading switch gear / protection system) Equivalent to major reinforcement costs (e.g. new line / new substations) High Medium Low Expected potential to defer major reinforcements to the network (e.g. new lines / upgrading or new substations etc.) Could help to reduce total investment costs on network for forecast integration of RES Improved performance and reduced operational costs (e.g. reliability, customer satisfaction) but no savings in capital expenditure can be identified High Medium Low Most benefits have been achieved and are supported by result from the demo Benefits partially achieved and are supported by results from the demo Benefits have either not been achieved or the results are not yet available from the IGG demo or any other demo projects Low Medium High No issues have been identified where regulatory conditions (existing conditions) or standardisation of technologies used that could have an impact on the economical / practicality of a large scale European deployment Regulatory conditions (e.g. ability for DSO to control injected power from PV at PCC) or standardisation issues requiring substantial costs would have to be resolved for successful deployment of the solution outside the demo Table 2 Preliminary evaluation deployment potential criteria Successful deployment of the solution being tested in the demo is dependent on existing infrastructure (e.g. ICT, AMI), without this it could be more economical to reinforce the network using new lines, upgrading substations etc. V /12/18 16/79

17 WP4: D4.2 A questionnaire was completed by the demonstration partners for each Use Case For the purpose of completing this evaluation, categories of solutions were developed based on the previous work of Use case definition that was completed in Work Package 2. The following categories of solutions were identified as representing the solutions being tested within the IGREENGrid demonstration projects: Anti islanding on MV networks. Customer engagement. Generation Forecasting for DG. LV Congestion management. LV Voltage Control. LV Voltage Monitoring. MV Congestion management. MV Voltage Control. MV Voltage Monitoring. 3.2 Results The preliminary evaluation was completed using the survey questionnaire and interviews with experts from all six IGREENGrid demonstration projects. The results can be summarized as follows: Step 1 (Is it in scope?) All of the IGREENGrid demonstration projects have EEGI label status. Further evaluation of the individual solutions that are being considered for IGREENGrid also show that they are addressing at least one EEGI Functional Objective. Step 2 (Can we model it?) All DSO partners have confirmed that all the data requirements defined by Work Package 5 can be met and this data can be provided, as required, to the IGREENGrid project for all the solutions that are being tested within the demonstration projects. Step 3 (Deployment potential) The results are summarised in table below. This is based on accumulation of feedback received from the survey questionnaire. The table provides a general picture based on the experience of the DSOs within IGREENGrid based on a majority perspective. The following should be noted: 1. Different networks have different requirements and these results, based on the majority opinion, do not mean that there will not be exceptions. For example, voltage control solutions are expected to be a requirement on LV networks in some countries and not others. This is mainly due to different levels of expected growth of DG on LV networks which is a direct result of government incentives and this can vary between different countries V /12/18 17/79

18 WP4: D This survey was carried out using the demonstration projects within IGREENGrid as reference. These are mainly rural networks and different results would be expected for urban networks 3. Anti-Islanding solution for MV networks was not considered to be relevant for this evaluation. The deployment of this type of solution would become mandatory if an anti islanding system for MV networks is required by the regulator 4. Customer engagement solutions are considered to be addressing both congestion and voltage profile problems on the network by encouraging customers to follow an optimum consumption profile 5. For Voltage control solutions there are vast differences in the level of investment required depending on what type of control system is used. Distributed control has much lower requirement for telecommunication system and hence would incur a lower investment and possibly operational cost when compared to a centralised control system, especially where new telecommunication infrastructure is a requirement. For the purpose of this summary, Voltage control solutions were given a medium deployment potential in when considering criterion 2 (Level of investment and operational costs associated with the solution in the demonstration project). It should be noted that distributed control system would have lower costs associated and should therefore be considered between medium and high deployment potential and vice versa for centralised control systems. This will be considered further in the detailed evaluation. The results are illustrated in Table 3 based on the following assumptions: 1. Continued growth of DG over next ten years. This is directly related to government incentive schemes and difficult to predict and the cause of some degree of uncertainty for DSOs 2. Costs of new technology in the demonstration projects may reduce given a large scale deployment scenario. Expectations from some of the demonstration projects show that, in some cases this reduction of cost would be necessary to make the solution a competitive alternative to deploying other technologies and in some cases to business as usual. V /12/18 18/79

19 WP4: D4.2 Deployment potential 1. Extent of problem being addressed by solution on networks considered in IGREENGrid 2. Level of investment and operational costs associated with the solution in the demonstration project 3. Expected economical benefits of the solution (not restricted to the demo project) 4. Extent to which the expected benefits are supported by results (IGREENGrid demo or others) 5. Expected level of risk on investment for large scale deployment (on a European scale) High Medium Low High Medium Low Voltage Control (MV and LV) Voltage Monitoring (MV and LV) Congestion management (MV and LV) Generation Forecasting for DG Customer engagement Low Medium High Voltage Monitoring (MV and LV) Generation Forecasting for DG Voltage Control (MV and LV) Congestion management (MV and LV) Customer engagement High Medium Low Voltage Control (MV and LV) Congestion management (MV and LV) Voltage Monitoring (MV and LV) Customer engagement Generation Forecasting for DG High Medium Low Voltage Control (MV and LV) Voltage Monitoring (MV and LV) Generation Forecasting for DG Congestion management (MV and LV) Customer engagement Low Medium High Generation Forecasting for DG Voltage Monitoring (MV and LV) Voltage Control (MV and LV) Customer engagement Congestion management (MV and LV) Table 3 Preliminary evaluation deployment potential results V /12/18 19/79

20 WP4: D4.2 The following order of most promising solutions, by category, was determined based on the expectations of deployment potential, economic, technical and regulatory feasibility. Order of most promising categories 1 Voltage Control (MV and LV) Category of solution 2 Voltage Monitoring (MV and LV) 3 Congestion management (MV and LV) 4 Generation Forecasting for DG 5 Customer engagement Table 4 Prioritisation by solution category from Preliminary Evaluation results From the Preliminary evaluation it was possible to determine the most promising categories of solutions to address DG integration. This selection was based on the expectations from the experience gained from the demonstration projects. For the type of networks considered within the IGREENGrid project, voltage control solutions are recognised as being those with the highest potential for addressing DG integration. The worst case scenario is under conditions of high generation and low load, where the reactive energy from the generation causes an increase in voltage along the feeder. Traditionally, with distribution networks dominated by loads and very little generation, the voltage profile of the MV network would be regulated using an OLTC on the transformers in the primary substation and this would be sufficient to maintain the voltage within contains at the secondary busbar. A problem with this approach occurs when you have different feeders, connected to the secondary busbar, some primarily connecting generation and others with primarily load connections. Under these circumstances there is a wide voltage band at the ends points of the different feeders. Potential under voltages are observed at the end of the feeders with primarily loads connected due to the deteriorating voltage along the feeder, while potential over voltages are experienced at the end of the feeder with primarily generation connected. In this situation, as illustrated in Figure 4 it is more difficult to maintain the voltage profile within limits using the OLTC transformer. Conventionally this problem could be addressed using booster transformers. Within most of the demonstration projects, control of the reactive power from the DG at the PCC was used first. V /12/18 20/79

21 WP4: D4.2 Figure 4 Voltage profile along feeder example There are a range of different approaches for voltage control in terms of the technology and type of control. These are summarised in Figure 5 below. For both MV and LV voltage control there are two main categories of solution: 1. Control system: a. Distributed: A distributed control system is where monitoring and control is implemented locally. The devices are self-regulating and each individual device is controlled autonomously. These solutions are considered to be the most economical in terms of investment and maintenance costs since no telecommunication infrastructure is required. However, this type of solution does have the limitation that there is no control on the overall reactive power. Although these solutions may be capable of maintaining voltage profile, the potential of low power factor under conditions of high compensation, could potentially create additional problems such increased losses in the supply. b. Supervised: Devices are controlled and coordinated locally, but with V /12/18 21/79

22 WP4: D4.2 communications link to a dispatching centre, which has the capacity to supervise the state as required (not real-time). This would allow a greater level of control compared to a distributed control system, but at a higher cost due to requirement for telecommunications infrastructure, if the telecommunication infrastructure does not already exist. c. Centralised: Set points are sent to each device from the dispatching centre using a coordinated control system. This approach allows a high level of control and it would be expected to have a greater impact on maintaining voltage profile. It is also possible to control the voltage while also considering other constraints, such as power factor. Due to the telecommunication requirements high investment and operation costs are expected, if the telecommunication infrastructure does not already exist. 2. Technology: a. OLTC transformer: These are common placed at primary substation and the distributed control of the OLTC on MV networks is considered as BaU. The performance can be improved by using a centralised control of the OLTC. As explained previously, the main limitation of controlling the voltage profile using the OLTC is in scenarios where there are feeders with primarily load and other feeders with primarily generation connected to the secondary busbar. The OLTC would not be capable of compensating for both under voltages and over voltages at the extremes of the relative feeders for load and generation respectively. OLTC are less common place at secondary substations and potential benefits for LV networks have been identified for some networks within IGREENGrid, using either distributed or centralised control systems. The resulting decoupling of the low voltage level from medium voltage one provides for medium and low voltage grids increased voltage range. b. Controlling DG: The voltage profile is maintained by regulating either the reactive or active power at the PCC. Given that this functionality is made standard for new PV / wind power installations then there would be potentially high economic benefits, especially for distributed control, given the low investment costs, if network reinforcements can be avoided as a result. However, for most countries in Europe the existing regulation does not permit the DSO to control the reactive or active power of DG. A case would have to be made for a review of existing regulation in order to realise any potential economic benefits using this technology. The DSO is required to balance reactive power. It cannot be neglected that voltage control using reactive power, requires additional reactive power. A solution to get a helpful provision for reactive power management from DG is needed. c. AVR: The voltage profile is controlled at the primary or secondary substation or along the feeders using an AVR device. The advantage of this approach, compared to an OLTC transformer, is the continuously variable voltage control as opposed to discrete steps. The AVR deployed in the German demonstration projects also represents a different approach compared to the other solutions for implementing voltage control. In the German demonstration project, the AVR is implemented as a temporary solution to bridge the gap between high levels of DG being connected to the network and the eventual requirement to V /12/18 22/79

23 WP4: D4.2 reinforce the network. The expectations are that after the network has been reinforced (upgrading or installing new cables and substations, i.e. BAU) there will be no more requirement for the voltage control solution and the AVR can be reinstalled at a different part of the network, as required. The AVR is designed to be transportable and can be relocated to different parts of the network. d. STATCOM: Although it is not a new technology, the STATCOM could be deployed in distribution networks to provide voltage control by regulating reactive power. The STATCOM can be used on either MV or LV networks using either distributed or centralised control systems. This solution could be considered as an alternative to the traditional booster transformer or controlling the DG. e. Storage: A controlled power flow from a storage facility can be used to regulate the voltage profile on the network. A range of different types of storage facility could be used but in the IGREENGrid demonstration projects using Li ion battery technology is most common and a CHP was used in the German demo. Figure 5 Overview of voltage control solutions Regarding the question of which technology should be deployed, the investment decision will ultimately be based on feasibility, in terms of standardisation, meeting regulatory requirements and economics. These aspects will be considered further in the detailed evaluation. As is the nature of power system development, the DSO plan the network based on expected requirements, in terms of new load and generation connections and forecast load and generation profiles. The performance of each technology is therefore a requirement that must be satisfied for the solution to V /12/18 23/79

24 WP4: D4.2 be considered. The most common approach for voltage control within the IGREENGrid demonstration projects is controlling the reactive power injected by the DG inverter at the PCC (Point of Common Coupling). Important feedback received from the demonstration projects includes the observation that reactive power works best on networks that consist mostly of overhead lines. The effectiveness of reactive power to control voltage profile is reduced at MV-level by the capacitance due to insulation and in MV- and LV-level by less inductive impedance of cables due to lower distance of wires. Given that both regulation and the difficulties in contracting new overhead lines, the drive is towards cables and this applies to even remote parts of the network in rural locations. In LV grids overhead lines with single wires provide less power quality due to lower reliability and higher impedance. A higher impedance in LV feeders also limits the current as the resulting fuse from limiting touch voltages in case of earth faults can be much lower than the rated current of the line. The limitation of these solutions for networks consisting of mainly cable feeders could be explored in WP5. If reactive power cannot be used effectively to control the voltage profile then active power regulation could be considered. The best way to investigate would be using simulation studies for a range of networks, different impendence profiles. i.e. substituting OHLs (Overhead lines) for cables. The detailed evaluation will consider a range of factors that would influence expected benefits, risks and feasibility, the deployment potential will have to be verified using simulation studies in WP5, considering performance of these different approaches on different networks and economic benefits compared to other options, such as BaU. Congestion management solutions were considered as important but given a lower deployment potential than voltage control because the first problem for DG integration for most of the networks considered within the IGREENGrid demonstration projects, was maintaining voltage profile. It should be emphasised that most of the networks within the IGREENGrid project are rural networks with low loads, high generation potential and relatively long feeders. Very different results would be expected from urban networks where it is more likely that network congestion would be the first bottle neck, before voltage violations have to be addressed. The economical benefit and feasibility of congestion management solutions would have then to be compared to reinforcing the network with larger or new cables and / or upgrading substations, to evaluate the deployment potential. A clear advantage of congestion management solutions over reinforcing the network would be the long lead times for replacing cables or upgrading substations. It is also becoming increasingly difficult to build new overhead lines and even in remote rural regions it is becoming necessary to use cables. The increased cost and lead times to install cables could also support the case for congestion management solutions. DG generation forecasting and voltage monitoring solutions are also considered to have a high deployment potential for addressing DG integration. This is based on potential economic benefits that can be realised by fully utilising the existing system through improved network operation and planning, along with relatively low costs and low risk on investment. Monitoring solutions were considered to be of particular relevance for LV networks where an increase in DG is expected. This is because, generally LV networks are less monitored than MV networks and due to their size and complexity of dynamic and asymmetric loads, less understood. By better understanding the network, new generation and load connections can be planned to optimise the existing capabilities. Particular opportunities were identified for LV networks where three phase connections are used for domestic properties. By using monitoring solutions, new connections can be planned to avoid V /12/18 24/79

25 WP4: D4.2 phase to phase imbalance which is detrimental to the voltage profile and increases the likelihood of voltage violations. A cost effective solution for monitoring LV networks would be utilising AMI provided that the meters have voltage monitoring functionality. This is currently not standard. Customer engagement solutions have been demonstrated to prove some support for smoothing the load curve and encouraging customers to follow DG generation profile. However, when compared to voltage control or congestion management, at present these solutions are generally not considered to have so much impact on deferring or preventing grid investment that needed for DG integration, at least for the networks considered within the IGREENGrid project. Customer engagement solutions are, however considered relevant to DG integration and maximising the utilisation of renewable energy when it is available. 3.3 Conclusions The results and feedback obtained from the demonstration projects using the survey questions, which was followed up by more detailed discussions with each demonstration project, provided a reasonable level of coherency. This is most likely due to the fact that most of the networks within the IGREENGrid demonstration projects have certain similarities. The projects are mostly implemented in rural areas on networks with light loading, relatively long feeders and with the potential for high levels of installed DG with respect to the load. Under these conditions, it is quite common that the first bottle neck for integrating DG is caused by a limitation on the amount of generation that is possible before the voltage limits are exceeded. Voltage monitoring and voltage control solutions for both MV and LV networks were identified as solutions that could show potential for realizing benefits over reinforcing the network, or the BaU approach. However, the full potential of these solutions would have to be better understood from a cost perspective using a CBA and comparing the results to BaU. Irrespective of which solution is implemented to address the problems caused by DG, the following factors were also identified as being critical for successful DG integration. These will be evaluated further in the Detailed evaluation. DG growth uncertainty: In order to facilitate DG integration it is necessary to develop solutions to maintain safe, economical and reliable operation within the statutory limits for security of supply, power quality etc.. These solutions could be using traditional network reinforcements such as new cables or upgrading substations or it could be the deployment of novel solutions using new technologies. Whichever solution is used, the successful implementation and integration of DG would be supported by a more gradual and predictable growth of DG on European distribution networks. Over the course of the last five years there have been cases of very rapid increase of DG followed by periods of reduced growth and uncertainty over future DG growth. This makes it more difficult for DSOs and other relevant stakeholders to plan the network and to find the most cost effective solutions. This problem could be addressed by more strategic incentive schemes that directly influence DG growth. The incentive schemes could also be used to determine where, within the network, the DG growth will occur. Network investment costs could be potentially reduced by utilising the existing capabilities of the networks to host DG. V /12/18 25/79

26 WP4: D4.2 Regulation: Given existing regulation in most European countries the DSO s cannot control the power injected into the network from DG. Within some of the demonstration projects, bilateral contracts are used with the DG customers and this is on a voluntary basis. Under these regulatory conditions there would be a high risk associated achieving the potential benefits from solution that require the control of either active or reactive power injected by the DG. Regulation change would be necessary for a large scale deployment of these solutions to be successful. Standardisation: Improved levels of standardisation would reduce investment risk and encourage private funding initiatives. Planning rules: Under current regulation and planning rules it is necessary for the DSO to plan the network to cater for worst case scenario and therefore could potentially lead to the requirement of reinforcing the network to allow new DG connections. Network reinforcements usually have high associated costs and where new cables or upgrading substations are concerned, can be subjected to lengthy timescales to complete the work. Cost uncertainty: Typically, within the demonstration projects, the new technologies are expected to have higher costs than what would be expected in a large scale market uptake scenario. In some cases, the reduction in cost of a technology, resulting from large scale manufacturing and competition between the suppliers, could be critical for the economic viability of the solution. It was identified from the demonstration projects that in many cases, there is a high degree of uncertainty associated with the future cost of the technology. This uncertainty could be addressed by using results from economic studies and modelling future markets for a range of deployment scenarios List of solutions for Detailed evaluation In the Preliminary Evaluation the solutions which were considered to show the most potential for addressing DG integration were selected by category. With this high level approach it was not possible to distinguish between similar solutions of the same category. To provide a selection of solutions from each category, a more detailed evaluation was completed and recommendations made for simulation studies for further evaluation in order to determine the most promising solutions. For the purposes of completing this evaluation it was decided, within the IGREENGrid consortium, to defined generic solutions based on those from the IGREENGrid demonstration projects as described in the Use Cases that were defined in Work Package 2 and are presented in Annex A of deliverable D2.1. The definition of these generic solutions is presented here. These definitions are based on the following assumptions: The solutions do not include retrofitting of DG installations. A new OLTC at MV/LV Substations implies removal of old MV/LV transformer and installation of a new one including OLTC control. A new connection point adaptation is required for big elements (Storage, STATCOM...). V /12/18 26/79

27 WP4: D MV Voltage Monitoring solutions These solutions address DG integration by improving the DSOs ability to plan and operate the network using voltage monitoring at MV MV Voltage Monitoring (PLF) This is a solution for smart network operation/planning using SCADA/Offline/AMI (whichever is available) and network state estimation. The solution consists on off-line studies for network status estimation using PLF, based on load and generation profiles, using offline voltage measurements. It is assumed that the use of AMI for aggregated data at the SS level if existing or some historical data and load and generation profiles MV Voltage Monitoring (RTU) This solution will provide smart network operation/planning using a few most relevant nodes. It utilises real-time measurements acquired from a selection of nodes using RTU. It is assumed that the RTU and telecommunications infrastructure already exists for most DSOs. The performance depends on the number of sensors already installed and the acquisition frequency rate MV Voltage Monitoring (SE) This solution will provide smart network operation/planning using a few of the most relevant nodes and a SE using V, I measurements. The load/generation profiles are not required. The state estimation algorithm uses real-time measurements from sensors located at the most relevant nodes within the network. It is assumed that the partially new sensors, an adapted or new telecom infrastructure and new software at the control centre level LV Voltage Monitoring solutions These solutions address DG integration by improving the DSOs ability to plan and operate the network using voltage monitoring at LV LV Voltage Monitoring (AMI) This solution consists on off-line studies using measurements from an existing AMI installed on the LV network. It is assumed that he existing meters have a voltage measurement capability. The solution also requires additional tools for forecasting load and generation profiles LV Voltage Monitoring (AMI+SE) This solution uses state estimation using real-time measurements from certain Smart Meters located at the most relevant points on the network. It is assumed that the Smart Meters are already installed and have capacity to send measurements in real-time using an existing telecommunication infrastructure. The solution will therefore require the deployment of software at the control centre It is expected that these solutions will only be required in problematic areas LV Voltage Monitoring (RTU) This solution uses real-time measurements using RTUs. It is assumed that installation of RTUs and adaptation of telecommunication infrastructure is required as part of the deployment of this solution. V /12/18 27/79

28 WP4: D LV Voltage Monitoring (SE) This solution consists of a state estimation using real-time measurements from sensors located on the most relevant points of the network. It is assumed that there will be a requirement for new sensors, an adapted or new telecommunications infrastructure and some new software at the control centre MV Voltage Control solutions These solutions address DG integration by providing voltage regulation on the MV network. This would improve the DSOs ability to maintain a voltage profile within the statutory limits with increasing levels of DG MV Centralised (field measurements) Voltage Control with OLTC This solution uses OLTC and a limited number of measurements in the most relevant points of the network both controlled and coordinated from a dispatching centre (DMS). It is assumed that the OLTC is already installed and the solution will require new measurements in critical places and a new or upgraded telecommunication infrastructure MV Centralised (SE & OPF) Voltage Control with OLTC This solution utilises an OLTC transformer at the Primary Substation and a reduced number of measurements at the most relevant nodes on the network. The change of tap position to regulate the voltage profile is both controlled and coordinated from a dispatching centre with the support of a SE & OPF. The main purpose of this solution is to maintains voltage profile within the statutory limits. Additionally it could also provide optimisation of performance (e.g. reduce losses). It is assumed that a transformer equipped with an OLTC is already installed at the primary substation. The deployment of this solution would therefore require the installation of new measurement equipment, new or adaptation of existing telecommunication infrastructure, and new software MV Centralised (SE & OPF) Voltage Control with OLTC & DG This solution is similar to the solution described in Section above with the addition of controlling the reactive power of the DG at the PCC. Control and coordination is received from a dispatching centre, with the support of a SE based on a few grid measurements and an OPF. An existing OLTC is assumed and the reactive DG control is paid for by generator. The solution would require new measurements in critical places, new or adaptation of existing telecommunication infrastructure and new software MV Centralised (SE & OPF) Voltage Control with OLTC & DG & STATCOM This solution is similar to the solution described in Section above with the addition of some STATCOM devices in critical places on the network. It is assumed that there are existing OLTC, reactive DG control paid by generator. The solution will require the installation of new measurements devices in critical places, new STATCOM, new or adaptation of existing telecommunication infrastructure and new software. V /12/18 28/79

29 WP4: D MV Centralised (SE & OPF) Voltage Control with OLTC & DG & Storage This solution is similar to the solution described in Section above with the addition of a storage facility MV Centralised (SE & OPF) Voltage Control with OLTC & DG active power modulation This solution is similar to the solution described in Section above with the addition that the DSO may ask for active power modulation if necessary (below 5% of total production). It is assumed that there will be economic compensation for active power modulation MV Centralised (SE) Voltage Control with OLTC This solution utilises an OLTC transformer at the Primary Substation and a reduced number of measurements at the most relevant nodes on the network. The change of tap position to regulate the voltage profile is both controlled and coordinated from a dispatching centre with the support of a SE. It is assumed that a transformer equipped with an OLTC is already installed at the Primary Substation. The deployment of this solution would therefore require the installation of new measurement equipment, new or adaptation of existing telecommunication infrastructure, and new software MV Centralised (SE) Voltage Control with OLTC & DG & Storage This solution is similar to the solution described in Section above with the addition of controlling the reactive power of the DG at the PCC and the installation of a storage facility. Control and coordination is established from a dispatching centre with the support of a SE MV Distributed Voltage Control with AVR Voltage control on the MV network is achieved by installing an AVR in critical places of the network. The unit is controlled independently of any dispatching centre. The deployment of this solution would require the installation of a new AVR including new measurements at the connection point. No telecommunications are required MV Distributed Voltage Control with DG active power modulation This solution consists of an autonomous regulation of the active power generated by the DG, using local voltage measurements, to maintain the voltage, at the connection point (or PCC), within a predefined target range. Each generator will have a threshold which are predetermined by simulation studies and dependent on the connection point. It is assumed that Active DG control functionality within the inverter is paid for by generator for the new installations. Economic compensation will be provided for active power modulation. No telecommunications are required MV Distributed Voltage Control with Local Storage A storage facility is used to regulate the voltage at the connection point (or PCC) using power flow modulation. Voltage measurement and control are implemented locally independent of any V /12/18 29/79

30 WP4: D4.2 dispatching centre. The implementation of this solution would require the deployment of one or more storage facilities installed at optimum locations on the MV network. New measuring devices would also be required at the point of connection. There is no requirement for telecommunication infrastructure MV Distributed Voltage Control with OLTC This solution utilises an OLTC transformer at the Primary substation and local voltage measuring device. The change of tap position to regulate the voltage profile is both controlled locally and independent of any control centre. It is assumed that a transformer equipped with an OLTC is already installed at the primary substation. The deployment of this solution would therefore require the installation of new measurement equipment and a local control device. No telecommunication infrastructure is required. This solution already exists on most distribution networks and it could be considered as Business as Usual (BaU). However, since there may be some cases where DSOs do not have this solution already implemented, some partners within the IGREENGrid consortium requested that this be included as a Solution Under Test (SUT) MV Distributed Voltage Control with OLTC, DG This solution uses an autonomously controlled OLTC (as described in Section above) and an autonomous control of the DG providing reactive power control to maintain the voltage profile within predetermined limits. It is assumed that the OLTC is already installed on the network and the DG inverters already have the functionality to provide reactive power control. For new installations this will be included in business model. If the DG has already been connected to the network and the existing installations do not have this functionality, then, in most cases, it is expected that retro fitting would not be considered as a viable option MV Supervised (field measurements) Voltage Control with OLTC & DG The OLTC and a limited number of measurements in the most relevant points of the network, both controlled and coordinated locally, independent from the dispatch centre (DMS) but the DMS has the capability to supervise the state when required but not in real-time. It is assumed that the OLTC is already installed and the solution will require new measurements in the most relevant places of the network and a new or upgraded telecommunication infrastructure. The inverters with a reactive power control functionality will be paid for by the generation customers as part of new installation. A new local control automation system would also be required MV Supervised Voltage Control with OLTC & DG This solution is similar to the solution described in Section above with only local voltage measurements LV Voltage Control solutions These solutions address DG integration by providing voltage regulation on the LV network. This would improve the DSOs ability to maintain a voltage profile within the statutory limits with increasing levels of DG LV Distributed Voltage Control with OLTC V /12/18 30/79

31 WP4: D4.2 This solution utilises an OLTC transformer at the Secondary substation and local voltage measurements. The change of tap position to regulate the voltage profile is both controlled locally and independent of any control centre. Transformers with an OLTC are not common in Secondary substations and it is assumed that replacing the existing transformer with an MV/LV transformer with an OLTC transformer would be part of this solution. There is no requirement for telecommunication infrastructure LV Distributed Voltage Control with AVR Voltage control on the LV network is achieved by installing an AVR at critical places of the network. The unit is controlled independently of any dispatching centre. The deployment of this solution would require the installation of a new AVR including new measurements at the connection point. No telecommunications are required LV Distributed (field measurements) Voltage Control with OLTC This solution is similar to the solution described in Section above with a limited number of measurements at the most relevant points of the network, both controlled and coordinated locally, independently from the dispatch centre (DMS) A local controller at SS manages OLTC from both local measurements and several LV network measurements LV Distributed Voltage Control with DG This solution uses regulates the voltage at the point of connection (PCC) using an autonomous control of the DG providing reactive power control. It is assumed that the DG inverters already have the functionality to provide reactive power control. For new installations this will be included in business model. If the DG has already been connected to the network and the existing installations do not have this functionality, then, in most cases, it is expected that retro fitting would not be considered as a viable option LV Distributed Voltage Control with OLTC, DG This solution results of a combination of the solutions described in Section and Section above. The control is autonomous and the DG and OLTC are independent of any dispatch centre (DMS). There is no requirement for telecommunications infrastructure LV Distributed Voltage Control with DG active power modulation Autonomous regulation of the active power generated by the DG, using local voltage measurements, to maintain the voltage, at the connection point (or PCC), within a predefined target range. Each generator will have a thresholds which are predetermined by simulation studies and dependent on the connection point. It is assumed that Active DG control functionality within the inverter is paid for by generator for the new installations. Economic compensation will be provided for active power modulation. No telecommunications are required LV Distributed (field measurements) Voltage Control with OLTC, DG The OLTC and a limited number of measurements at the most relevant points of the network, both V /12/18 31/79

32 WP4: D4.2 controlled and coordinated locally, independent from the dispatch centre (DMS). Transformers with an OLTC are not common in Secondary substations and it is assumed that replacing the existing transformer with an MV/LV transformer with an OLTC transformer would be part of this solution. There is no requirement for telecommunication infrastructure. The inverters with a reactive power control functionality will be paid for by the generation customers as part of new installation. A new local control automation system would also be required LV Distributed Voltage Control with STATCOM Voltage control on the LV network is achieved by installing a STATCOM at critical places of the network. The unit is controlled autonomously and independent of any dispatching centre. The deployment of this solution would require the installation of a new STATCOM including new measurements at the connection point. No telecommunications are required. If an OLTC exists they will work independently LV Supervised (field measurements) Voltage Control with OLTC & DG The OLTC and reactive power control of the DG are used to maintain voltage profile. A limited number of measurements in the most relevant points of the network, both controlled and coordinated locally, independent from the dispatch centre (DMS) but the DMS has the capability to supervise the state and coordinate when required but not in real-time. It is assumed that the OLTC is not already installed and it will be part of the deployment of this solution to replace the existing MV/LV transformer with a new transformer with an OLTC. and the solution will require new measurements in the most relevant places of the network and a new or upgraded telecommunication infrastructure. The inverters with a reactive power control functionality will be paid for by the generation customers as part of new installation. A new local control automation system would also be required LV Centralised (SE & OPF) Voltage Control with OLTC & DG & This solution utilises an OLTC transformer at the Secondary substation, control of the reactive power from the DG and/or other devices (storage, AVR,..) and a reduced number of measurements at the most relevant nodes on the network, with control and coordination from a dispatching centre with the support of a SE & OPF. This solution would require a new OLTC transformer at the Secondary substation and/or the new installation of AVR, STATCOM, etc, the installation of new measurement equipment, new or adaptation of existing telecommunication infrastructure and new software. The inverters with reactive power control functionality will be paid for by the generation customers as part of new installation MV Congestion Management solutions These solutions address DG integration by providing regulation of the active power generated by the DG and/or by using energy storage solutions on the MV network. This would improve the DSOs ability to avoid congestion problems resulting from increasing levels of DG and deferring or avoiding the need for grid expansion. V /12/18 32/79

33 WP4: D MV Congestion Management with DG non-firm grid connection contracts (including DG modulation) The DSO sends set points for modulation DG generation as planned on the connection contracts. To put in place this solution the adaptation of existing connection studies (in order to determine the conditions of the DG modulation) is needed. It is assumed that new DG equipped for modulation is paid by generators MV Congestion Management with Use of Flexibility (DG, DSM, STR...) All kind of flexibilities that a DSO may contract through a market platform : modulation of generation, Demand side management, Storage, Aggregators... The existence of these third parties, communications needed, economic compensation for the services and market platform (short term, long-term) is assumed LV Congestion Management solutions These solutions address DG integration by providing regulation of the active power generated by the DG and/or by using energy storage solutions on the LV network. This would improve the DSOs ability to avoid congestion problems resulting from increasing levels of DG and deferring or avoiding the need for grid expansion LV Congestion Management with DG non-firm grid connection contracts (including DG modulation) The DSO sends set points for modulation DG generation as planned on the connection contracts. To put in place this solution individual DG connection studies needed for each generator and new centralized control system for the LV network (SCADA, SE, OPF... ) are needed. It is assumed that the new DG equipped for modulation is paid by generators LV Congestion Management with Use of Flexibility (DG modulation, DSM, STR...) All kind of flexibilities that a DSO may contract through a market platform : modulation of generation, Demand side management, Storage, Aggregators, Electric Vehicles. It is assume that there are these third parties, communications needed, economic compensation for the services, a market platform (short-term, long-term)and a new centralized control system (in order to check the effectiveness of the use of the flexibility to solve the congestion). V /12/18 33/79

34 WP4: D4.2 4 Detailed evaluation The solutions selected from the Preliminary evaluation were evaluated using a qualitative evaluation to assess the feasibility, expected benefits and risks associated with a large scale deployment on a European scale. The results from the IGREENGrid KPIs are also presented and these are used to validate the conclusions based on the performance expectations from the qualitative evaluation. 4.1 Qualitative evaluation A qualitative evaluation was completed using the experience of the IGREENGrid partners to evaluate each solution using concepts that are considered to be crucial for successful deployment and realizing benefits for the integration of DRES Methodology For the qualitative evaluation, the following concepts were considered: 1) Performance 2) Social Aspects 3) S&R 4) Reliability 5) Risk on Investment 6) Technical Complexity 7) Technical Requirements 8) Regulatory and Market Requirements 9) Economical Requirements In order to perform the analysis based on the aforementioned concepts, its definition has been agreed. Also in some cases these concepts are defined using some characteristics for each concept. The criteria to evaluate these characteristics are explained in the following sections because the differences in the nature of the concepts evaluate do not allow using the same criteria Performance The performance expectations of each solution were evaluated, based on the experience gained from the demo projects and distribution systems for each of the DSO partners. In each group of solutions the approach has been to evaluate the level of accomplishment of the particular task of the group and the usefulness or efficacy for the global objective of all proposals which is integrating renewable sources. The concept of accuracy has been included through the capacity to use real-time information for their calculations or estimations. The completeness is considered through the amount of information used for the monitoring or the amount of elements V /12/18 34/79

35 WP4: D4.2 controlled for active implementations. Linked also with completeness and accuracy the idea of wideness of the area involved in the resolution of the problem (voltage control has been considered, because the feed-back from the demonstrations (Italy and Austria) shows that centralized systems covering a wider area are expected to achieve a high level of performance (regulating voltage at LV,...) Social Aspects Within this section, social aspects of solutions have been evaluated. This took into account the impact of new construction requirements on local areas. The need for customer participation is also recognised where collaboration is needed to realise the expected benefits from the solutions. For example, the requirement to maintain the voltage level is perceived as a problem of the utility and not of the consumer, the perception of safety risk for the presence of new elements in the neighbourhood that get a bad press and on the other hand a positive perception of being contributing to a better environment. Also the security of supply is an important social issue. As customers can be affected differently by interruptions depending on different network topology in case of decreasing reliability customers will not accept different quality levels of supply. Aspects related to the worsening of their living environment (such as noise, pollution, space required...) are found and the perception by the customer is that the DSO is operating customer s equipment and could have a responsibility on the bad performance or damages on their PV panels or their domestic installations Scalability and Replicability A key factor to analyse the different solutions proposed to integrate renewable sources is the facility to be scaled up and replicated. There are multiple factors impacting on these two aspects. Probably the most critical one could be the need of communications to implement a certain solution, because it implies a lot of additional specialized work and infrastructures to be deployed. For similar reasons the amount of elements to be installed (sensors, RTU,...), its size or the space needed for the new equipment are also relevant factors. On the other hand, a high level of standardization of a solution and its elements may facilitate enormously the work of expanding it. Regulation requirements, the need of modifying contracts, etc have been also considered Reliability For the reliability we defined the following categories are defined: I. Unplanned outages for the following types of failure: i. ICT ii. Devices iii. Control system The reliability will be evaluated by considering the following for each type of failure a. Impact on system functionality caused by a failure b. Probability of failure c. Outage time (Fault restoration time) V /12/18 35/79

36 WP4: D4.2 II. Planned outages / maintenance schedule. This could be an evaluation of any reduced functionality of system caused by disruptive or consideration of the required maintenance schedule Risk on Investment The Risk on investment is a consideration of factors that currently propose a risk on realising the economic benefits that justify the investment today or uncertainty about the future. The main contributing factors to the risk on investment were considered to be as follows, Cost uncertainty Regulatory uncertainty Standardisation risk 1. Cost uncertainty The uncertainty associated with the cost of new technology during the market uptake phase could present a risk to the economic viability of the solution. Scores will be allocated as follows: LOW: New technology with high costs in demo. The current cost of the technology would not make large scale deployment economically viable, however, it is expected that, at a market uptake phase, with an increased market for the technology and competition between manufacturers, the cost of the technology will come down to a level that would permit economical deployment. Due to a current lack of information what the cost will be, a high risk level is associated with cost uncertainty. : An increased certainty over future cost of technology or current cost is close to level that would make a large scale deployment of the technology economically viable. : Reasonable level of certainty that future cost of technology / existing. 2. Regulatory uncertainty There are also risks associated with uncertainty over future regulatory conditions that could influence the effectiveness of the solution. Scores will be allocated as follows: LOW: No regulation at all. : Some regulation. : Clear regulation. 3. Standardisation risk This is the risk associated with investing in the deployment of new technologies without existing standardisation (either regional or European). LOW: No existing standardisation (either locally or at European level) for technologies deployed in solution. Or b) Solution does not comply with existing standards (either locally or at European level). And, it is expected that substantial costs would be incurred to upgrade / develop interface to comply with future/existing standards. : a) or b) from above and it is expected that the cost of upgrading / developing new interfaces to comply with future/existing standards is negligible. Or, all technologies used within solution are compliant with existing standards at national level but not at European level (it could be that there are no existing standards at European level). : All technologies used within solution are compliant with existing standards at European level. V /12/18 36/79

37 WP4: D Technical Complexity Three levels of technical complexity were considered, System level Component level Interoperability 1. Technical complexity at system level It considers the number of systems that make up the SUT (e.g. ICT (telecommunications, management systems, SE, PLF, etc), measurement devices, controllable devices (OLTC, STATCOM, DG, CHP, Storage, etc). The higher the number of systems is the higher the technical complexity and therefore the lower the rating in terms of deployment potential. LOW: Solution is made up of, or dependent on, the existence of many different systems (e.g. centralised control system: measuring devices, communications, control, electrical components). : Solution in made up of a limited number of systems (e.g. field measurements: measuring devices, communications). : Solution is self contained (e.g. distributed control using self regulating PV invertors). 2. Technical complexity at component level It is similar to the above but at component level. E.g. several DGs VS one OLTC/STATCOM, many monitoring devices vs a reduced optimal number of monitoring points. LOW: Solution consists of many components (e.g. distributed voltage control using many PV invertors). : Solution consists of moderate number of components (e.g. small number of field measurement devices and a transformer). : Solution consists of a small number of components (e.g. OLTC and SE). 3. Interoperability complexity for new technologies Do we need new interfaces? This can increase level of complexity especially where there is no existing standardisation LOW: New interface requirements / standardisation are required. Medium: New interface requirements that could be covered by existing standardisation. : No new interface requirements Technical Requirements The following categories of technical requirements were identified: 1. Large number of measurements needed : No additional measurements. : Some measurements (less than 5 per Primary Substation). LOW: Very large number. 2. Implementation of a central control system V /12/18 37/79

38 WP4: D4.2 Centralized systems are more demanding in terms of requirements. A central control system is more complex than a distributed one. : There is a distributed or not control system. : There is a central control system. 3. Monitoring and control of end-users' devices The distribution network operation, based on DSO owned devices, is straightforward but when customer (end-user) devices (inverters, meters ) are involved there will be further needs. : DSO not monitors end-user devices. : DSO monitors end-user devices. LOW: DSO control end-users devices. 4. Installation and operation of non-standard equipment The physical location of the device and any special requirements are also considered here. We consider also the technical integration (for example in the DMS). : Only standard equipment is used. : If the non-standard equipment is used. 5. Uni/Bidirectional communications : No communication needed. : Uni-directional. LOW: Bi-directional. 6. Type of communications Communications are normal DMS pulling times (in the range of 15 minutes). Hard read time needs as those used for protection are not considered. : No communication needed. : On-demand/on-event communication. LOW: Periodically communication. 7. Time requirement for the system : No communication needed. : More than 15 minutes. LOW: Less than 15minutes. 8. Bandwidth : Low bandwidth (less than 1 Mbits/s). LOW: High bandwidth (more than 1Mbits/s). 9. Number of types of Standards of communication needed Is there any standard? For instance, controlling MV devices would be probably based on IEC /104 or but each LV PV inverter manufacturer could be providing private communications if any. : Vendor or DSO specific communication protocol by device to be control. : One standard communication protocol by device type to be controlled. LOW: Several standard communication protocol by device type to be controlled. V /12/18 38/79

39 WP4: D Cybersecurity Are there any special requirements? For instance, telecommunication operators provide virtual private networks over public channels (GPRS, LTE...) and therefore there would not be any additional need to cypher the communications. : No specific cybersecurity requirement is needed. : DSO needs a specific cybersecurity requirement. 11. Coordination and control of high number of devices The complexity of the solution increases with the number of controlled devices, for instance a large number to MV DG along the MV feeders. : No additional devices. : Some devices (tens per Primary Substation). LOW: Very large number (hundred per PS). 12. Retrofit old devices (e.g. inverters) to support new functionalities The solution may require some functionalities that are not available on already deployed devices, for instance, reactive power control on inverters as a function of the local measured voltage. : Not retrofit is needed. : A component retrofit is needed by installation. LOW: Several components need to be retrofit by installation. 13. Standardization of smart grid components Some of the elements included in the solution may be innovative devices (i.e. STATCOM) so there are no previous experiences. : Not use new devices. : New devices don t used yet by the DSO but already deployed in other sectors (TSO...). LOW: Use of prototypes (not really industrial products) Regulatory and Market Requirements The following factors were considered for the evaluation of the deployment potential based on regulatory and market requirements of each solution: 1. MV National existing Grid code for DRES A new clear regulation defining the grid codes (technical requirements in terms of functionality, capacity, communications, etc.) is needed. For instance, MV DGs may be requested to provide Q=f(U) or P=f(U), to include some standard communication protocol for updating the off-set, etc. : No control. : Q control for DG. LOW: Q and P control for DG. 2. LV National existing Grid code for DRES V /12/18 39/79

40 WP4: D4.2 A new clear regulation defining the grid codes (technical requirements in terms of functionality, capacity, communications, etc.) is needed. For instance, LV PV inverters may be requested to provide Q=f(U) or P=f(U), to include some standard communication protocol for updating the offset, etc. : No control. : Q control for DG. LOW: Q and P control for DG. 3. Regulation for reactive power, voltage control, curtailment, etc. provision The regulation should define the general framework for service provision. There could be different alternatives leading to different implementations of the solution. For instance, if DRES are required to follow curtailment orders assuming the role of the DSO as independent network operator or this is a contracted and negotiated service. Incentives encouraging the participation of DRES in the provision of ancillary services could also be possible if the service provision is optional for DRES owners. : No control. : Regulatory driven (modification of connection code). It s a compulsory service that will be provides. LOW: Market driven. 4. Regulation for energy storage systems There should be a clear regulation regarding the type of services that energy storage systems can provide, market arrangements, ownership. : No storage installed. : Not specific regulation is required for storage. LOW: Specific regulation for a storage system use or connection is required. 5. DSO should be allowed to access to the required information In some countries there are special restrictions to the use of some network data (i.e. customer demand) for network operation purposes. : Solution doesn t need individual load curves or measurements at the individual customer level. : Solution only needs aggregated load curves or measurements. LOW: Solution needs individual load curves or measurements at the individual customer level. 6. Definition of TSO and DSO roles The limits between TSO and DSO are not clear, in some cases the TSO may request services from the DG/Active Demand that enter into conflict with the DSO needs. For instance, requesting reserve power affecting the DG/AD power injection/consumption and leading to distribution network constraints. : Solution can t be affected by an additional TSO request at the distribution connected resources (DG, AD, ) level. : Solution can be affected by an additional TSO request at the distribution connected resources (DG, AD, ) level. V /12/18 40/79

41 WP4: D Economical Requirements These requirements define the relative importance of the expenditures needed to implement the solution. In order to better justify this importance we have identified the possible cost sources of the solutions (for the moment we don t estimate the exact value of these sources). These cost sources have been classified in order to facilitate this task following the criteria below: CAPEX: Inside the CAPEX, the elements could include (and/or) studies, new equipment, modification of existing equipment and installation. For this reason, when considering the deployment potential of the solutions, we use is used to indicate that it s necessary for a new element and when is only necessary modify, upgrade or refurbish. It is assumed that a modification is less expensive than a new element. Also in this category the following sub-categories have been included: o o o Equipment/Hardware. Software. Communications. OPEX: An assigned deployment potential of would indicate that this cost is needed and none when it s not needed. Distribution retribution. The economical requirements consider the following aspects: CAPEX Equipment/Hardware Software OLTC transformer in MV/LV OLTC transformer in HV/MV Specific modifications in the generators in case are not able to provide the services V/I Sensors Electrical Storage (Battery) Energy Storage (Non-Battery, e.g. Bio Gas) DER Local Controller Storage Controller STATCOM MV STATCOM LV Electrical infrastructure modifications to install device (e.g. necessary for STATCOM, BATERY...) AVR MV AVR LV SCADA Space for Installation MV State estimator algorithm LV State estimator algorithm Probabilistic / Optimal power flow algorithm Voltage VAr Control Solution (VVC) within the SCADA Topology processor algorithm V /12/18 41/79

42 WP4: D4.2 Load Forecast algorithm DER Production Forecast algorithm Development of software tool for Maintenance (Asset Management) Telecommunication with inverter and OLTC Telecommunication with Smart meters Communications Telecommunication with Secondary Substation. Telecommunication with DG Telecommunication with new devices Software Maintenance Telecommunication Training of the staff Additional staff OPEX Individual configuration Periodical verifications Retribution to the DER owners Auxiliary consumptions of devices Maintenance costs of equipment Space Renting Distribution retribution Table 5 Categories of capital and operational costs considered for qualitative evaluation of economic requirements for each solution It is extremely important to note that, as real costs are not considered in the calculation the comparison among the absolute values makes no sense at all. Only the relative orders should be considered Results The solutions identified from the preliminary evaluation were further evaluated based on the concepts described in Section and a rating was given for the expected deployment potential. The results, along with a justification for the allocated deployment potential are presented here for each implementation category. The results from this evaluation can be found in Annex B of the WP4 D4.2 Annex document Conclusions The deployment potential of each solution was determined by aggregating the scores allocated for each category and an average score was calculated. For simplicity it was assumed that each category had an equal impact on the deployment potential of the solutions. Based on this assumption, each category was given an even weight when calculating the average. The average values were calculated by expressing the deployment potential scores numerically. The aggregated scores for the deployment potential are illustrated in Table 6 below. Due to the high level of uncertainty associated with the costs of new technologies at the deployment phase, it was decided V /12/18 42/79

43 WP4: D4.2 not to include the Economic Requirements parameter to calculate the average score for deployment potential. A CBA will be included in the further evaluation of the selected solutions in Work Package 5. The collective knowledge, experience and expectations of each DSO partner were used to complete this evaluation. The evaluation was based upon today s system in terms of existing infrastructure and existing or foreseen requirements on the distribution systems. It is also based on today s regulatory conditions, existing market frameworks and today s cost expectations of the new technologies. It should be emphasised that there is a certain amount of uncertainty associated with some of the topics considered. This is described in more detail in Section 3.3. The average deployment potential of the solutions was sorted in descending order per Functionality to obtain those with the highest scores. The results from this evaluation are illustrated in Table 6 below. The following conclusions were obtained for each category of solution. MV Voltage Monitoring The highest scoring solution for MV Voltage Monitoring was using PLF with off line field measurements. This approach has been used, to some extent, for many years for short term and long term network planning. If voltage monitoring is to be used for network management and closer to real time, there could be potential benefits in using real time data and this could be achieved using solutions with data from RTUs or using a SE. However, the results from this evaluation to not support the investment that would be needed to implement these solutions solely for the use of network planning or operations. This might of course change as levels of DG increase and a higher degree of flexibility in terms of network operation is required. However, actual gains in potential HC of DG could only be achieved with revised planning rules where reconfiguration of the network is considered. At present it was not possible to conclude with any certainty that this would be the case or whether the requirement would exist. The MV Voltage Monitoring solutions using RTU or SE may be a requirement for other solutions such as Voltage control, congestion management or automation. LV Voltage Monitoring One of the main challenges for LV monitoring is the high rate of voltage fluctuations with respect to MV and these results in the requirement for a higher sampling rate. There is also a requirement for three phase measurements which will also increase the amount of data that has to be captured, transmitted or stored and processed. It is therefore expected that the communications bandwidth or memory storage and data processing requirements would be very high compared to similar solutions that are developed for the MV network. A good solution would be to use AMI to provide voltage profile monitoring, using statistical data to reduce bandwidth/memory /data processing requirements. A solution providing data only for relevant intervals regarding maximum & minimum or certain percentiles of voltage levels all over the LV-grid would perfectly meet the requirements in respect to network planning as well as privacy of customers (e.g. Austria Power Snapshot analysis). However, it should be noted that a voltage monitoring function are not standard for meters. Also, V /12/18 43/79

44 WP4: D4.2 access to meter data could also be an issue in some countries where DSO is not responsible for metering, need to request this data. (e.g. Germany, UK), have to request each customer. At present, capturing voltage measurements is not a standard functionality of smart meters and there are cases where distribution networks already have an AMI installed that does not have a voltage measuring functionality. Due to the scale and the complexity of most LV networks, other solutions for LV voltage monitoring using real time data from either RTUs or a SE were not considered to be cost effective to implement solely for the purpose of network planning. Opportunities were highlighted from the Austrian demonstration project were potential benefits could be realised by using the voltage data from the smart meters to better understand the characteristics of the network and hence, identify network areas in which voltage violations might occur and focus the investments accordingly. In Austria where three phase connections are used for domestic properties, potential problems with voltage profile and phase to phase imbalance can be reduced by careful selection of which phase to connect single-phase PV roof top installation (concept proposed in the Austrian demo). Given that an AMI with voltage measuring capabilities already exists, this could be done very cost effectively and the potential benefits could largely outweigh the costs. MV Voltage Control On medium voltage networks, voltage control solutions using both distributed and centralised control could be considered to address what is considered to be the first bottle neck for integrating DG on rural distribution networks. The most sensible approach would be to first try to address the problem using the OLTC and where it is no longer possible to maintain the voltage within the statutory limits other solutions could be considered and compared to BaU using a CBA. LV Voltage Control The AVR voltage control solution in German demo offers a different approach than the other demos. Bridge the gap instead of smarter grid.. Ultimately network reinforcements are considered to the solutions to addressing most problems associated with voltage profile and network congestion caused by DG. The application of novel solutions, such as the AVR with a distributed control system which is designed to be a temporary solution that can provide cost savings by deferring network reinforcements. It is considered that once the network has been reinforced, there will no longer be a requirement for the voltage control solutions. The AVR is designed to be transportable to different locations on the network so it can be reused as required. The approach for addressing voltage profile problems within all the other demonstration projects is based on the permanent implementation of novel technologies and ICT. These two different approaches could be compared by considering the evolution of several networks over a given time horizon and ultimately the evaluation would be based on a CBA. MV Congestion Management The use of non firm grid connection contracts was considered to offer the highest deployment potential for addressing network congestion, as a result of DG integration, in the short to medium term. Currently participation is based on a voluntary basis and regulation change would be needed to reduce the uncertainty over the potential benefits of these solutions. Other solutions implementing Lithium-Ion storage, as demonstrated in several of the IGREENGrid demonstration projects would need to reach a higher level of maturity in terms of regulatory conditions, market V /12/18 44/79

45 WP4: D4.2 frameworks and cost of technology before they could be considered as a feasible option for large scale deployment and an economically viable solution for addressing DG integration. The use of flexibility needs to define an appropriate market framework and an appropriate regulation framework in order to define how the DSO will be cover its costs generated by the economic compensation to be paid to the aggregators for the services provided. LV Congestion Management Similar to the MV Congestion Management, the use of non firm grid connection contracts was considered to offer the highest deployment potential for addressing LV network congestion. However, additional regulatory requirements are needed for both in the majority of the European countries. DG connections contracts are often defined with a fit and forget approach and the active power curtailment are not allowed. In addition, the use of flexibility needs to define an appropriate market framework and an appropriate regulation framework in order to define how the DSO will be cover its costs generated by the economic compensation to be paid to the aggregators for the services provided. V /12/18 45/79

46 WP4: D4.2 Functionality Implementation Performance Social Aspects MV Voltage Monitoring LV Voltage Monitoring MV Voltage Control LV Voltage Control MV Congestion Management LV Congestion Management Table 6 Deployment potential using aggregated scores from qualitative evaluation Tech. Regulatory Econ. MV Voltage Monitoring (RTU) LOW MV Voltage Monitoring (SE) LOW LOW MV Voltage Monitoring (PLF) LV Voltage Monitoring (AMI) LV Voltage Monitoring (RTU) LOW LV Voltage Monitoring (SE) LOW LV Voltage Monitoring (AMI+SE) LOW LOW MV Centralised (field measurements) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG LOW MV Centralised (SE & OPF) Voltage Control with OLTC & DG & STATCOM LOW LOW LOW LOW LOW MV Centralised (SE & OPF) Voltage Control with OLTC & DG & Storage LOW LOW LOW LOW LOW LOW LOW MV Centralised (SE & OPF) Voltage Control with OLTC & DG active power modulation LOW LOW LOW LOW MV Centralised (SE) Voltage Control with OLTC LOW MV Centralised (SE) Voltage Control with OLTC & DG & Storage LOW LOW LOW LOW LOW LOW LOW MV Distributed Voltage Control with AVR MV Distributed Voltage Control with DG active power modulation LOW MV Distributed Voltage Control with Local Storage LOW LOW MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Supervised (field measurements) Voltage Control with OLTC & DG LOW LOW MV Supervised Voltage Control with OLTC & DG LV Distributed Voltage Control with OLTC LOW LV Distributed Voltage Control with AVR LV Distributed (field measurements) Voltage Control with OLTC LV Distributed Voltage Control with DG LV Distributed Voltage Control with OLTC, DG LV Distributed Voltage Control with DG active power modulation LOW LV Distributed (field measurements) Voltage Control with OLTC, DG LV Distributed Voltage Control with STATCOM LOW LV Supervised (field measurements) Voltage Control with OLTC & DG LOW LOW LOW LV Centralised (SE & OPF) Voltage Control with OLTC & DG & LOW LOW LOW LOW MV Congestion Management with DG non-firm grid connection contracts (including DG modulation) LOW LOW LOW MV Congestion Management with Use of Flexibility (DG, DSM, STR...) LOW LOW LOW LOW LOW LOW LOW LV Congestion Management with DG non-firm grid connection contracts (including DG modulation) LOW LOW LOW LOW LOW LOW LOW LV Congestion Management with Use of Flexibility (DG modulation, DSM, STR...) LOW LOW LOW LOW LOW LOW LOW LOW Scalability and Replicability Reliability Risk on Investement Deployment Potential Tech. Complexity Requirements Avergae V /12/18 46/79

47 WP4: D4.2 Functionality Implementation Average score from qualitative evaluation MV Voltage Monitoring (PLF) MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) LV Voltage Monitoring (AMI) LV Voltage Monitoring (SE) LV Voltage Monitoring LV Voltage Monitoring (AMI+SE) LV Voltage Monitoring (RTU) MV Distributed Voltage Control with AVR MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC MV Centralised (SE) Voltage Control with OLTC MV Distributed Voltage Control with DG active power modulation MV Supervised Voltage Control with OLTC & DG MV Voltage Control MV Centralised (SE & OPF) Voltage Control with OLTC & DG MV Supervised (field measurements) Voltage Control with OLTC & DG MV Distributed Voltage Control with Local Storage MV Centralised (SE & OPF) Voltage Control with OLTC & DG active power modulation MV Centralised (SE & OPF) Voltage Control with OLTC & DG & STATCOM MV Centralised (SE & OPF) Voltage Control with OLTC & DG & Storage MV Centralised (SE) Voltage Control with OLTC & DG & Storage LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with AVR LV Distributed (field measurements) Voltage Control with OLTC LV Distributed Voltage Control with STATCOM LV Distributed Voltage Control with DG LV Voltage Control LV Distributed Voltage Control with OLTC, DG LV Distributed Voltage Control with DG active power modulation LV Distributed (field measurements) Voltage Control with OLTC, DG LV Supervised (field measurements) Voltage Control with OLTC & DG LV Centralised (SE & OPF) Voltage Control with OLTC & DG & MV Congestion Management with DG non-firm grid connection contracts MV Congestion (including DG modulation) Management MV Congestion Management with Use of Flexibility (DG, DSM, STR...) LV Congestion Management with DG non-firm grid connection contracts LV Congestion (including DG modulation) Management LV Congestion Management with Use of Flexibility (DG modulation, DSM, STR...) Table 7 Average deployment potential by 'Functionality' category sorted from high to low LOW LOW LOW LOW LOW V /12/18 47/79

48 WP4: D Quantitative Evaluation using KPIs The quantitative evaluation of the solutions tested within the DEMOs has been carried out by means of the Key Performance Indicators proposed in [D2.2]. In spite the original methodology has been designed in order to process the measurement data provided by the real demonstration activities, according to the practical limitations highlighted in [D2.3] and [D4.1], a simulation-based approach has been adopted. The details of the simulated scenarios and KPIs calculation procedure are discussed in the IGREENGrid KPIs Report document. According to the goals of IGREENGrid, the main KPI selected for the evaluation of the performance of solutions is: Increase of DRES Hosting Capacity, which measures the ability of the solution to increase the amount of installable generation in the considered network. Secondly, in order to monitor the side effects of the technologies connected to the smart grid solutions, other two indicators have been added to the main list of KPIs. In particular they have been categorized as: Improvement of Quality of Supply, which measure the impact of the solution on the voltage profile when it is applied on the considered network; Increase of energy efficiency, which evaluate the impact of the solution on the technical energy losses of the considered distribution network. In the following paragraph the resulting KPIs of solutions tested within the DEMOs are listed and discussed KPIIGG.1 Increase of DRES Hosting Capacity The main goal of IGREENGrid is to identify the most promising solution for a reliable integration of DRES in distribution networks. According to this, the hosting capacity increase (attributable to the application of smart grid solutions) represents the most relevant indicator for the evaluation of the technical performance of a given technology. According to IGREENGrid KPIs Report document, simulations have been carried out by considering several scenarios in which the future generation is randomly allocated in the studied networks (Monte Carlo simulation). In this way, a solutions is used to feature different performance values depending on the position of DG units and, in the following tables, the average increase of Hosting Capacity and the impact that the size of the DG units and the connection point of the DG on the network, has on the performance results are reported. V /12/18 48/79

49 WP4: D4.2 DEMO Solution Average Value [%] Variability GERMANY MV centralized voltage control with field measurements - OLTC SPAIN MV centralized voltage control - OLTC + STATCOM control AUSTRIA MV supervised voltage control with field measurements - OLTC + DG reactive power control AUSTRIA MV supervised voltage control with field measurements - OLTC control GERMANY MV distributed voltage control with AVR FRANCE MV distributed voltage control - DG reactive power control (droop Q-V control) FRANCE MV distributed voltage control - DG reactive power control (fixed tan(phi)) ITALY MV supervised voltage control - OLTC + DG reactive power control SPAIN MV centralized voltage control - STATCOM control GREECE MV distributed voltage control - DG curtailment + DG reactive power control GREECE MV distributed voltage control - DG curtailment Table 8 Increase of DRES hosting capacity experienced in IGREENGrid DEMO projects (MV solutions) DEMO Solution Average Value [%] Variability AUSTRIA LV supervised voltage control with AMI AUSTRIA LV distributed voltage control with AMI AUSTRIA LV distributed control - OLTC + DG reactive power control GERMANY LV distributed voltage control with AVR Table 9 Increase of DRES hosting capacity experienced in IGREENGrid DEMO projects (LV solutions) From the analysis of the results it can be immediately recognized that most of the ICT based solutions (centralized and supervised) are featuring the highest performance, achieving about +62% of Hosting Capacity increase in both MV and LV demonstrators. On the contrary, the lowest (but still positive) performance is featured by distributed solutions, with an average HC increase of +26% and +38% in MV and LV respectively. Looking at tables above, two exceptions can be identified: The Spanish solution (centralized voltage control with STATCOM) is performing an hosting capacity increase typical of distributed control strategies. The divergence with other centralized solution is justified by the limited contribution provided by a single STATCOM device. In fact, by only adding the contribution of the OLTC, the expected hosting capacity increase results more in line with other ICT-based controllers. The Italian solution is performing a hosting capacity increase typical of distributed technologies. This divergence highlights an important aspect that has to be carefully considered during the evaluation of KPIs: the network dependency. In fact, from the practical application of the KPIs formula, it has been immediately recognized a strong influence of the network parameters (lines length, voltage level, load profile and allocation) on the resulting performance indication. From the KPI results, other relevant information can be extracted. According to the data reported in Table 63 and 64, some conclusion on the dependency between hosting capacity increase and DRES allocation can be drawn. In general, it can be noticed that the influence of generators position on the KPI is low for centralized solutions and it increases for distributed technologies. V /12/18 49/79

50 WP4: D KPIIGG.2 Improvement of Quality of Supply The main effect of the studied technologies is identifiable as a reduced impact of DRES on the voltage profile of the network. For this reason, the improvement of the quality of supply (mainly voltage quality) has been monitored in order to evaluate the benefits of the solution in terms of voltage regulation. In order to evaluate the performance of the solutions in different operating conditions of the network, the same random allocations of DRES considered for the Hosting Capacity calculations have been used. In addition, two situations of high penetration of DRES have been evaluated IGREENGrid KPIs Report document: Uncritical situation: high DRES integration that can be tolerated by the network even without the solution support; Critical situation: high DRES integration that cannot be tolerated by the network and smart grid solutions are required. According to the simulation approach used for the evaluation of this KPI, the definition of voltage quality can be applied only to MV solutions. From the performed simulations, executed as described in IGREENGrid KPIs Report document, the results related to MV solutions are reported in the following table. DEMO Solution Uncritical situation Critical situation GERMANY MV centralized voltage control with field measurements - OLTC SPAIN MV centralized voltage control - OLTC + STATCOM control AUSTRIA MV supervised voltage control with field measurements - OLTC + DG reactive power control AUSTRIA MV supervised voltage control with field measurements - OLTC control GERMANY MV distributed voltage control with AVR FRANCE MV distributed voltage control - DG reactive power control (droop Q-V control) FRANCE MV distributed voltage control - DG reactive power control (fixed tan(phi)) ITALY MV supervised voltage control - OLTC + DG reactive power control SPAIN MV centralized voltage control - STATCOM control GREECE MV distributed voltage control - DG curtailment + DG reactive power control GREECE MV distributed voltage control - DG curtailment Table 10 Improvement of Quality of Supply experienced in IGREENGrid DEMO projects (MV solutions) From the KPI results it can be noticed that, in general, centralized and supervised solutions seem to guarantee higher voltage benefits with respect to distributed technologies. One of the exceptions is represented by the Spanish solution for which it can be stated that: In case of uncritical situation, the control flexibility is used for the reduction of power losses and the network is intentionally not operated at the nominal voltage. This is perceived as a negative KPI but it does not mean that the solution decreases the performance of the network: in fact, when voltage limits are fulfilled there is not a definition of voltage quality. In case of critical situation, the controller acts on the network flexibility in order to limit the voltage variations that determine violation of the operational limits. In this case, as expected, the KPI is positive and it indicates the ability of the solution to reduce the voltage impact of DRES in case of necessity. V /12/18 50/79

51 WP4: D4.2 Another exception is represented by the solution tested in the French DEMO (DG reactive power injection with fixed power factor). This high KPI can be justified by the fact that DRES are injecting reactive power even when the voltage magnitude has not to be necessarily adjusted: this strategy results in a very limited impact of the DRES on voltage profile and, consequently, the KPI is very high in both uncritical and critical situations KPIIGG.3 Increase of Energy Efficiency Most of the investigated solutions are mitigating the effects of DRES on the voltage profile by increasing the injection of reactive power. Also in this case, the random allocation of DRES is simulated in bot critical and uncritical situation, and the results are reported in the following tables. DEMO Solution Uncritical situation [%] Critical situation [%] GERMANY MV centralized voltage control with field measurements - OLTC SPAIN MV centralized voltage control - OLTC + STATCOM control AUSTRIA MV supervised voltage control with field measurements - OLTC + DG reactive power control AUSTRIA MV supervised voltage control with field measurements - OLTC control GERMANY MV distributed voltage control with AVR FRANCE MV distributed voltage control - DG reactive power control (droop Q-V control) FRANCE MV distributed voltage control - DG reactive power control (fixed tan(phi)) ITALY MV supervised voltage control - OLTC + DG reactive power control SPAIN MV centralized voltage control - STATCOM control GREECE MV distributed voltage control - DG curtailment + DG reactive power control GREECE MV distributed voltage control - DG curtailment Table 11 Increase of energy efficiency experienced in IGREENGrid DEMO projects (MV solutions) DEMO Solution Uncritical situation [%] Critical situation [%] AUSTRIA LV supervised voltage control with AMI AUSTRIA LV distributed voltage control with AMI AUSTRIA LV distributed control - OLTC + DG reactive power control GERMANY LV distributed voltage control with AVR Table 12 Increase of energy efficiency experienced in IGREENGrid DEMO projects (LV solutions) For this KPI it is not easy to divide the solutions in different categories. However, the following conclusions can be deduced from the results: The integration of devices in series to network branches (i.e. AVR), determines high impacts on power losses. In order to limit the effect on power losses, reactive power injection should be avoided when it is not necessary to compensate overvoltage events (difference between fixed power factor and Q(U) control strategies). Taking into account the intermittent nature of DRES, control actions are not necessary at every time step. In this case, the usage of network flexibility could be optimized in order to reduce energy losses when it is not necessary to solve network congestions. This would of course be subject to appropriate regulation and market framework. V /12/18 51/79

52 WP4: D KPIs results conclusions and targets In the previous paragraphs the KPIs results related to the solutions tested in demonstration projects have been listed. The application of the same calculation approach and the common network/solution modelling assumptions has increased the comparability of the results. However, the following limitations for the application of KPI methodology for the comparison of IGREENGrid solutions have to be taken into account: Simulations models are not available for all the considered solutions. Some of the smart grid strategies have not been implemented in real demonstrators but they have been deduced from other projects and/or recommended by stakeholders. In spite of the adoption of an harmonized calculation procedure, KPIs seems to be strongly affected by the network boundary conditions (loading level, grid characteristics, loads distributions, etc.). Taking into account this last point, practical experience shows that a comparison of solutions from demonstration projects to determine those with the highest large scale deployment potential cannot be exhaustively completed by means of KPIs. Although KPIs could be a useful tool to evaluate certain performance criteria when applying similar solutions to the same network, when evaluating the scalability and replicability of solutions from different demonstration projects and their potential for large scale deployment, an approach that is more representative an investment decision making process would be expected. This approach would include medium to long term network planning, a cost benefit analysis and risk assessment. Other criteria such as environmental impact, social acceptance should also be considered. However, on the basis of the KPIs results obtained for solutions tested in IGREENGrid demonstrators, some approximate targets can be deduced and reasonably expected from the application of smart grid strategies in distribution networks. Taking into account the primary objective of IGREENGrid, the most relevant target to define is represented by the hosting capacity increase (KPIIGG.1). According to the previous paragraphs, and having excluded the few exceptions, this KPI seems to identify some clusters of solutions for which the hosting capacity increase can be expected to be: Cluster of MV solutions % increase of HC Dependency on DRES position Solutions based on centralized control low Solutions based on supervised control medium Solutions based on distributed control high Table 13 Targets of DRES Hosting Capacity Increase for MV solutions Cluster of LV solutions % increase of HC Dependency on DRES position Solutions based on supervised control high Solutions based on distributed control medium/high Table 14 Targets of DRES Hosting Capacity Increase for LV solutions V /12/18 52/79

53 WP4: D4.2 5 Most Promising solutions In terms of assessing the deployment potential of different solutions, the KPI results were used in conjunction with the conclusions from the qualitative evaluation described in Section 4.1. The deployment potential of a solution would be determined by several factors, including feasibility, risk on investment and economics. The feasibility was evaluated within the qualitative evaluation by considering topics such as technical requirements, social acceptance and scalability and replicability. Other topics such as standardisation and regulatory requirements addressed the risk on investment. The economic requirements were also considered and the performance, as represented by the KPIs would contribute to the economic benefits which would ultimately be evaluated using a CBA. A quantitative evaluation of these factors will be completed in Work Package 5 using a CBA. The technical performance represented by the IGREENGrid KPIs would be considered as factor that would contribute towards the economic benefits that would be realised by the deployment of the solution. For these reasons the KPI results alone were not used for the selection of solutions. The KPI results were used to validate the expectations from the qualitative evaluation. The results from the qualitative evaluation described in Section 4.1 were combined with the results from a survey asking the DSO partners which solutions they would to offer the most potential for deployment in the short to medium term. Although high rating were achieved in the detailed evaluation, two of the solutions developed in the German demo using AVR units on the MV and LV network were not included in the list of solutions to be studied further in WP5. This is because these solutions represent a different approach, where instead of presently implementing new technology on the network, new technologies and control systems, in this case autonomous control systems, are used as a temporary solution to defer network reinforcements. Ultimately it is expected that network reinforcements will be need and the AVR is engineered to be portable and it is possible and it is expected to be practical to relocate the AVR to different place on the grid, as required. Although this solution has not been included for WP5 it received high scores in the assessment that was competed and it would be recommended that DSOs do consider this as an option when planning their networks. V /12/18 53/79

54 WP4: D4.2 Functionality Implementation Average score from qualitative evaluation Votes from DSO survey MV Voltage Monitoring LV Voltage Monitoring MV Voltage Control LV Voltage Control MV Congestion Management LV Congestion Management MV Voltage Monitoring (PLF) 71% MV Voltage Monitoring (RTU) 57% MV Voltage Monitoring (SE) 86% LV Voltage Monitoring (AMI) 86% LV Voltage Monitoring (SE) 29% LV Voltage Monitoring (AMI+SE) 14% LV Voltage Monitoring (RTU) 14% MV Distributed Voltage Control with AVR 57% MV Distributed Voltage Control with OLTC 71% MV Distributed Voltage Control with OLTC, DG 86% MV Centralised (field measurements) Voltage Control with OLTC 71% MV Centralised (SE & OPF) Voltage Control with OLTC 86% MV Centralised (SE) Voltage Control with OLTC 86% MV Distributed Voltage Control with DG active power modulation 43% MV Supervised Voltage Control with OLTC & DG 57% MV Centralised (SE & OPF) Voltage Control with OLTC & DG 57% MV Supervised (field measurements) Voltage Control with OLTC & DG 43% MV Distributed Voltage Control with Local Storage 29% MV Centralised (SE & OPF) Voltage Control with OLTC & DG active power modulation 29% MV Centralised (SE & OPF) Voltage Control with OLTC & DG & STATCOM 43% MV Centralised (SE & OPF) Voltage Control with OLTC & DG & Storage LOW 29% MV Centralised (SE) Voltage Control with OLTC & DG & Storage LOW 29% LV Distributed Voltage Control with OLTC 86% LV Distributed Voltage Control with AVR 43% LV Distributed (field measurements) Voltage Control with OLTC 43% LV Distributed Voltage Control with STATCOM 14% LV Distributed Voltage Control with DG 43% LV Distributed Voltage Control with OLTC, DG 57% LV Distributed Voltage Control with DG active power modulation 43% LV Distributed (field measurements) Voltage Control with OLTC, DG 43% LV Supervised (field measurements) Voltage Control with OLTC & DG 14% LV Centralised (SE & OPF) Voltage Control with OLTC & DG & 0% MV Congestion Management with DG non-firm grid connection contracts (including DG modulation) 57% MV Congestion Management with Use of Flexibility (DG, DSM, STR...) LOW 57% LV Congestion Management with DG non-firm grid connection contracts (including DG modulation) LOW 43% LV Congestion Management with Use of Flexibility (DG modulation, DSM, STR...) LOW 0% Table 15 Results from Qualitative evaluation and DSO survey From this evaluation the following short list of solutions were proposed for further study in Work Package 5. Recommended implementations for further study in WP5 MV Voltage Monitoring/ MV Voltage Monitoring (PLF). MV Voltage Monitoring (RTU). MV Voltage Monitoring (SE). V /12/18 54/79

55 WP4: D4.2 LV Voltage Monitoring/ LV Voltage Monitoring (AMI). MV Voltage Control/ MV Centralised (field measurements) Voltage Control with OLTC. MV Centralised (SE & OPF) Voltage Control with OLTC. MV Centralised (SE & OPF) Voltage Control with OLTC & DG. MV Centralised (SE) Voltage Control with OLTC. MV Distributed Voltage Control with OLTC. MV Distributed Voltage Control with OLTC, DG. MV Supervised (field measurements) Voltage Control with OLTC & DG. MV Supervised Voltage Control with OLTC & DG. LV Voltage Control/ LV Distributed (field measurements) Voltage Control with OLTC. LV Distributed Voltage Control with DG. LV Distributed Voltage Control with OLTC. LV Distributed Voltage Control with OLTC, DG. MV Congestion Management/ MV Congestion Management with DG non-firm grid connection contracts (including DG modulation). MV Congestion Management with Use of Flexibility (DG, DSM, STR...). More detailed descriptions of these solutions are provided in Annex D where a further evaluation was completed for the Scalability and Replicability Analysis. V /12/18 55/79

56 WP4: D4.2 6 Scalability and Replicability Analysis (SRA) The study is focused on the solutions that have been highlighted as the most promising ones to address DRES integration into distribution networks after carrying out a qualitative analysis of them. The approach defined for this purpose is based on the assessment of the impact/importance of a specific set of Scalability and Replicability parameters on each solution. The study is carried out for a set of different scenarios representing different implementation options regarding Scalability and Replicability where the variables solution s scale size (scalability) as well as location and time frame (replicability) are modified. The output of the analysis is displayed as a set of radial graphics that allow a multi-criteria evaluation of the scalability and replicability potential of the different solutions in each scenario. This section includes the work carried out within T4.2 regarding the assessment of the potential for scalability and replication of the smart grid solutions developed by the demonstration projects involved in the IGREENGrid project and that have been highlighted as the most promising ones for addressing DRES integration. This work will be used as a starting point for the evaluation that will be completed in WP5. It was not used to influence the selection of solutions or recommendations that were developed in WP4. A more detailed description of the solutions, as selected in Section 5 can be found in Annex C. 6.1 Methodology 6.1 Overview of the methodology Before defining the approach, the concepts Scalability and Replicability should be clarified: Scalability is defined as the extension to which a solution can be brought to a bigger area within the same region. Replicability is defined as the extension to which a solution can be brought to a distant geographical area or to a different time period. The Scalability and Replicability Analysis (SRA) presented in this document is aimed at estimating the potential for scalability and replicability of the identified most promising solutions in a predefined set of S&R scenarios. The approach defined for the estimation of the S&R potential of each solution is based on the evaluation of a set of parameters related to S&R according to the impact/importance of each of them on the solution: the higher the score, the higher the potential for S&R. The methodology compares the value of the mentioned parameters for the considered solutions. With the aim of making it easier the assignment of the scores, the solutions are firstly ordered among them V /12/18 56/79

57 WP4: D4.2 following the assessment criteria presented in chapter Afterwards, a score varying from 0 to 10 is provided to each of them based on the assigned ranking. The analysis is performed for three different S&R scenarios representing different implementation options regarding scalability (changes on the solution s scale size) and replication (changes on the location and/or time frame). The study is carried out for each group of solutions aimed at the same objective, that is, that implement the same functionality (e.g. MV Voltage Monitoring, MV Voltage Control ). All solutions comprised within the same group are considered as different implementations of a specific functionality. The study is therefore focused on identifying the implementations that show higher potential for scalability and replication for each functionality S&R Scenarios Taking into account the different dimensions in terms of scalability and replicability (scale s size, location, time frame) three different scenarios can be defined: Scenario ID Scenario Name Scale s size Location Time frame SCN.IGG.01 Scalability in density Large scale Demo region Today SCN.IGG.02 Replicability (Today) Large scale Distribution network Today SCN.IGG.03 Replicability (Future) Large scale Distribution network Future Table 16 S&R scenarios overview Scalability in density - SCN.IGG.01: The demonstration may be fully representative of the real situation but in general it represents a reduced version of it used as a probe of concept. For instance, instead of monitoring and controlling every single Distributed Generator (DG) above 1 MW, only a subset or a superset of those could have been integrated in the demonstration. So, this scenario represents the deployment of the solution scaled-up to the actual size defined for the solution (larger scale) in the same distribution network type as the demonstration project. This could mean higher Distributed Renewable Energy Sources (DRES) penetration levels, higher degree of network automation. This scenario evaluates the applicability of the solution in the same network type as demo project (e.g. MV rural networks). Replicability (Today) - SCN.IGG.02: It exposes the applicability of the solution to a distribution network today in the same country as demo as well as in other EU countries. This means that, if for instance the solution is aimed to rural networks and rural networks represent only a 1% of the distribution network of the considered country, then the solution may not be widely deployed outside this network type. This scenario also analyses the international replicability of the solution by comparing the differences on the evaluation carried out by DSOs from different countries. These differences can be motivated by different boundary conditions such as market and regulatory framework, DRES types and penetration levels, distribution networks characteristics, etc. Replicability (Future) - SCN.IGG.03: This scenario is similar to SCN.IGG.02 but it is focused on a near future. It takes into account how market and regulatory conditions are expected to evolve in the considered countries (regulation schemes and incentives, economic situation, strategies from policy makers and distribution companies ) as well as other boundary conditions such as the forecasted penetration level of DRES. For instance, if LV Photovoltaic (PV) systems are expected V /12/18 57/79

58 WP4: D4.2 to increase then LV active power based voltage control solutions may be more needed in the future than nowadays. Figure 6 includes a graphical representation of the scenarios considered in the study: Figure 6: S&R Scenarios As it will be explained later in more detail in the data gathering process described in Annex D, the replicability of the solutions (SCN.IGG.02 and SCN.IGG.03) are evaluated in parallel for all considered countries because each participating DSO is asked to carry out the evaluation of the solutions thinking on the conditions of its respective country S&R Parameters The proposed SRA evaluates the scalability and replicability potential of the different solutions by means of the assessment of a set of parameters affecting scalability and replication. These are the following ones: 1. Relevance: it measures the necessity of the solution in the considered scenario (problem solved). 2. Assets: it refers to the technological components (devices, applications ) required for the deployment of the solution in the considered scenario. It measures the technical simplicity of solution implementation. 3. Requirements: it evaluates the simplicity to overcome the identified technical, economic, and regulatory requirements for solution implementation in the considered scenario. 4. Economy: it is related to the cost of the Assets and provides and evaluation of the economic viability of solution implementation in the considered scenario. 5. Risks: it evaluates the technical, economic and regulatory risks impacting the solution in the considered scenario. V /12/18 58/79

59 WP4: D4.2 For each solution implementation, a qualitative assessment of the previously described parameters in each scenario is carried out by giving them a score that varies from 0 to 10 according to the assessment criteria presented in Table 17. The higher the score, the higher potential for scalability and replication. Before the assignment of the score the implementations are relatively ordered among them (ranking) with the aim of making it easier the evaluation process. Parameter Relevance Assessment criteria How important is the objective that the solution is aimed at? (necessity of the solution) Assets How simple (technically) is the deployment of the required assets for solution implementation? Requirements How simple is the overcome of the requirements? Economy How viable economically is the assets deployment? Risks What is the impact of the risks on the solution? Score 0 (Low) (Medium) (High) Not very important. The solution is not expected to be required in the considered scenario or is expected to be required in very few occasions. The assets deployment is very complex (new devices/measureme nts/communications are required to build the solution from scratch). The requirements overcome are very complex. The assets deployment is hardly economically viable The impact of the risks on the solution is very high. Solutions with lower potential for S&R Intermediate importance. The solution is expected to be required in several occasions in the considered scenario The assets deployment has an intermediate complexity (e.g. devices/measureme nts/communications are partially deployed but may require further adaptations). The requirements overcome have an intermediate complexity. The assets deployment has an intermediate cost The impact of the risks on the solution is intermediate Solutions with intermediate potential for S&R Very important. The solution is expected to be required very often in the considered scenario The asset deployment is very simple (e.g. devices/measur ements/commun ications are already there, only integration is needed). The requirements overcome are very simple. The assets deployment is economically viable The impact of the risks on the solution is very low Solutions with higher potential for S&R Table 17 Parameters assessment criteria General concepts and conventions Types of Control Three basic forms of control are considered: Centralized: The central controller manages in real time the controlled devices requiring continuous bidirectional communication channels. V /12/18 59/79

60 WP4: D4.2 Supervised: It is a particular case of centralized control in which the central controller follows in real time the system evolution and updates, if needed, the controlled device parameterization. Distributed: Each device has its own local control in charge of following the electrical variables and acts accordingly. For instance the Q=f(U) for a LV PV inverter. Naming of the solutions The naming scheme at many of the solutions and implementations is formed by: Voltage level. The possibilities are: { MV LV } Control type: Three main alternatives: { Centralized Supervised Distributed } Between parenthesis the tools in place: State Estimator (SE), Optimal Power Flow (OPF). Control objective: There are two {Voltage Current} Control. Alternatively to Control Constraints Management could be more general. Starting with the word with the list of main elements under control. The & links devices controlled altogether in a coordinated manner (i.e. OLTC & DG); The, links devices under control but not coordinated among them (i.e. in OLTC, DG the local control of the OLTC is independent from the DG local reactive power control E.g.: MV Centralized (SE & OPF) Voltage Control with OLTC & DG The naming scheme for the functionality Monitoring is done by: Voltage level. The possibilities are: { MV LV } Voltage Monitoring In between parenthesis the list of main elements used (i.e. SE, PLF) E.g. MV Voltage Monitoring (SE) Voltage Monitoring is related to improve network observability. There could be alternative variables to be monitored for other purposes such as monitoring fuse status on secondary substations for faster restoration and improved customer support could be considered but they are discarded for this study. Other uses of better monitoring like condition based maintenance, local balancing of demand and generation, etc. are also discarded. The naming scheme for other solutions and implementations tries to be as descriptive as possible Outputs of the SRA Outputs of the SRA are presented in a matrix summarising the overall assessment carried out for each implementation in each scenario (Figure 7). V /12/18 60/79

61 WP4: D4.2 Figure 7 Overall assessment matrix The rankings/scores assigned to the parameters of the different implementations in each scenario are displayed finally as radial graphics. These allow carrying out a multi-criteria evaluation of the S&R potential of the different implementations in each scenario. It is important to note that it is not going to be possible to select a single solution as the best one from the S&R point of view for all countries. Many other factors such as the specific network characteristics of the country, the market and regulatory conditions prevailing, the particular philosophy of the DSO Company, etc. influence the decision of choosing one solution among others. So this analysis is out of the scope of this work. A sample radial graphic with illustrative purposes for SCN.IGG.01 Scalability in density in presented in Figure 8. Figure 8 Sample overall assessment graphic V /12/18 61/79

62 WP4: D Results The detailed results of the SRA, with justification of the allocated scores can be found in Annex E. 6.3 Conclusions The conclusions of the SRA for each category of solutions is presented here MV Voltage Monitoring Solutions Figure 9 includes a graphical representation of the multi-criteria evaluation carried out for the different MV Voltage Monitoring implementations in the three considered scenarios. Figure 9 Multi-criteria evaluation of MV Voltage Monitoring implementations (Average values) V /12/18 62/79

63 WP4: D4.2 The main conclusions drawn from the analysis are the following ones: [IBERDROLA (Spain)] According to their opinion, the PLF implementation for the MV monitoring solution is a well-known approach that allows to know and to understand better the network state with an affordable cost, but due high variability in the network parameters (V, I, P, Q,...) that introduce the DRES, it is necessary to have a tool to monitor/manage in real time the network, although this tool could not arrive to bring the same performance than others and it could be higher. The importance of when we could receive the information increases in a high penetration of DRES scenario. For these reason the PLF approach could be easier to deploy and consequently to have a higher potential for scalability and replication, but due the new necessities derived from the DRES introduction, we expect a wide deployment of SE. [GNF (Spain)] In GNF s opinion, state estimation is a key component for any number of smart grid applications on the distribution system. These include reactive power management, outage management, loss reduction, demand response, adaptable over-current protection, condition-based maintenance, distributed generation dispatch, integration with transmission system operations, and more. For this reason, we understand that the solution based on SE is the most suitable for MV monitoring, even if the cost, risks and requirements are higher than the other solutions. [ENEL (Italy)] Network monitoring solutions for MV networks, for the purpose of providing data for network operation and planning are currently in place in Italy and the data is readily accessible using the existing SCADA system. For the purpose of network operation and planning, off-line computer based simulations using PLF are currently used for state estimation. The need for real-time measurements with increasing accuracy, as well as accurate generation and load forecasting will become more critical as the complexity of the network operation increases with increasing DRES presence. A cost-benefit analysis would have to be completed to justify high investment costs associated with increased accuracy and low latency real-time measurements solutions for this purpose. Generally this is considered to be more critical for solutions, such as network automation, where the data is needed, in real time for controlling the network. High bandwidth, low latency communications infrastructure would incur an increased cost that might not be justified for operational, planning applications alone. It is likely that the existing system, using the SCADA, would be sufficient and more emphasis would be placed on accurate generation and load forecasting tools. [ERDF (France)] French medium voltage is already automated. Several measurements (RTU) are already installed on the network. Using these measurements it s possible to calculate the voltage drop through the feeder in a static way. The performance of this calculation is reduced with the integration of DG. It s necessary to improve the voltage monitoring in order to be able to detect the voltage constraints. For that in France they test a DSE. This DES needs some additional measurements (less than five per feeder) and a modification of the SCADA system including the SE software. This kind of solution is adapted to the networks with a high DG penetration. For the other we can continue to use the RTU for the monitoring purposes. V /12/18 63/79

64 WP4: D4.2 [SAG & NETZÖO (Austria)] The benefit from use of monitoring data for grid operation in respect to hosting capacity for DG and loads is depending on the accuracy needed. In case a day ahead PLF is sufficient, a state estimation based on real time loads with related costs is not economic (because of additional cost without benefit). The increasing relevance of SE for replicability as well as its dominant part for scalability expresses the common DSO opinion that state estimation might be the most effective method of monitoring. As in future SE is deemed to include also voltage measurement results on the long run it can be expected that a combined solution of field measurements and State Estimation supported by measured voltage levels will be the highest performing. Such systems can be implemented step by step within rollouts of remote-controlled and automated secondary substations LV Voltage Monitoring Solutions Figure 10 includes a review of the multi-criteria evaluation carried out for the LV Voltage Monitoring (AMI) implementation. Figure 10 Multi-criteria evaluation of LV Voltage Monitoring implementations (Average values) V /12/18 64/79

65 WP4: D4.2 The main conclusions drawn from the analysis are the following ones: [IBERDROLA (Spain)] The AMI implementation for the LV monitoring brings a reasonable performance with a relative low cost (always taking into account a previous deployment of smart meters). In the LV grid the introduction of DRES produces a necessity of information mainly at the secondary substation level, due that the reaction to manage the LV normally are produced here. Considering that the opportunities to monitor the LV network (at actually is not monitored) that this implementation gives we consider that will be deployed in all the networks that are equipped with smart meters. [HEDNO (Greece)] Smart metering (AMI) is the cornerstone for future smart grids. Smart meter deployment aims at improving grid operations and customer services. Advanced metering infrastructure enable utilities to reduce maintenance costs, suffer shorter grid outages etc. However, smart meter deployment requires huge investment and must therefore be optimized. Moreover, privacy protection must be fully assured for the processing of personal data by smart metering systems, as outlined by the European Commission recommendations. Italy (ENEL) has already completed the roll-out, while other countries (e.g. Spain) are under the deployment of several smart metering projects. [ERDF (France)] In the case of France smart meters they do not record voltage measurement. This means that this implementation is not feasible in France. Its deployment would require the individual modification of meter parameters and an extensive additional data centres. Due to this reason this implementation has not been evaluated by the French DSO. In any case if the AMI infrastructure allows to measure the voltage, the off-line calculation using this data () could help to detect the eventual voltage constraints with a minimal cost. [SAG & NETZÖO (Austria)] As Smart Meters have to be installed additional functions of local voltage measurement are easily to be implemented. Therefore replicability and scalability is high. To achieve the expected benefits, proper integration to all relevant systems has to be performed. The major part of the challenge is probably the interface to the network planning tools or even SCADA. Resulting OPEX have to be regarded within cost benefit analysis MV Voltage Control Solutions Figure 11 includes a graphical representation of the multi-criteria evaluation carried out for the different MV Voltage Control implementations in the three considered scenarios. V /12/18 65/79

66 WP4: D4.2 Figure 11 Multi-criteria evaluation of MV Voltage Control implementations (Average values) The main conclusions drawn from the analysis are the following ones: [IBERDROLA (Spain)] For IBERDROLA (Spain) the solution that it could be easily replicated is the ones based on a Distributed architecture built over OLTC transformers. To include other devices that contribute to the voltage control contributes to improve the performance of the solutions, but due the regulatory uncertainties it s not clear that these devices (Batteries, STATCOMs, Inverters...) could be used. Additionally the use of different types of devices in the same network needs some kind of coordination, which complicates the deployment of this kind of mixed solutions. But it is clear that the better performance of the centralized implementations could justify its deployment. Finally, they do not want to discard the other types of implementations (Batteries, AVR, V /12/18 66/79

67 WP4: D4.2 STATCOM...) because of its portability, they could be used as temporary solutions. [GNF (Spain)] In GNF (Spain) s opinion, active management, composed by centralized systems across the MV network, in association with an appropriate active control scheme, is the best implementation in order to operate the networks in the future. This could make it possible to monitor the network and issue signals to generators to match their output to a range of network states, having the mutual benefit of allowing additional embedded generation to be connected to distribution networks, at the same time as avoiding major network reinforcement. [ERDF (France)] ERDF (France) considers that Distributed Voltage Control solutions can help to solve many voltage constraints at low cost. In fact, MV Distributed Voltage Control with OLTC is already implemented in France. MV Distributed Voltage Control with OLTC, DG could help to solve additional constraints in the case of DG connected to non-dedicated feeders for little additional cost. In addition, centralised solutions including a SE are also very relevant for them. These solutions would require more investment than distributed ones but could help to solve more important constraints. These solutions would also provide better monitoring of the networks. Centralised solutions including DG would give the DSO more control over the voltage and would be especially useful to deal with DG connected to a dedicated feeder. So, to sum-up, ERDF considers that voltage constraints caused by DG connected to non-dedicated feeders could be solved via distributed solutions while the voltage constraints caused by DG connected to dedicated feeders would require centralised solutions with SE and DG control ( MV Centralised (SE & OPF) Voltage Control with OLTC & DG). [ENEL (Italy)] In Italy, ENEL are currently deploying MV voltage control solutions in demonstration projects. These solutions improve the operational flexibility of the network and could potentially increase the amount of DG that can be connected to the network without violating the voltage limits. The voltage control solutions that are being deployed within the Italian demonstration projects consist of OLTC and controlling the DG. Under the present regulatory framework it is not possible to control the power injected by the DG customers. Within the demonstration projects, the reactive power is controlled to regulate the voltage profile and this is dependent on voluntary participation of the DG customers. Although voltage control can be achieved using an OLTC transformer at the primary substation, in some cases it may be necessary to control the DG. For example, where there are radial feeders, from the secondary busbar, some supplying predominantly loads and other that have predominantly generation. In this example a wide voltage bandwidth would be seen at the secondary busbar and an OLTC might not be able to maintain the voltage profile with the required limits. Although traditionally these types of problems would be solved the installation of booster transformers, controlling the reactive power injected by the DG is an alternative approach. The control system used within the Italian demonstration project is both local and coordinated. The coordinated control would provide a greater degree of control over the voltage profile and could avoid discriminating certain DG customers who are connected at less optimal locations on the network. However the coordinated control system required a communications infrastructure and a centralised control system, resulting in higher investment and operational costs. V /12/18 67/79

68 WP4: D4.2 [SAG & NETZÖO (Austria)] By averaging assignments of involved DSO results are rather homogenous. Reasons behind might be different focus and experiences from demonstrations. SAG and NETZOÖ have been focusing on voltage control (Demo LUNGAU/SAG UC.AT.01) involving existing DG-plants and comparing Centralized control including SE and OPF integrated to SCADA with simple centralized control linked to SCADA. The SCADA integrated solution including SE and OPF over all seems to be the most promising with respect to the benefits for hosting capacity and operational purposes LV Voltage Control Solutions Figure 12 includes a graphical representation of the multi-criteria evaluation carried out for the different LV Voltage Control implementations in the three considered scenarios. Figure 12 Multi-criteria evaluation of LV Voltage Control implementations (Average values) V /12/18 68/79

69 WP4: D4.2 The main conclusions drawn from the analysis are the following ones: [IBERDROLA (Spain)] In the case of the LV network due to its extension and the cost of the necessary assets to deploy it they consider that it is very difficult to scale these solutions, except to where a specific problem appear (e.g.: long feeders with a lot DRES). [ERDF (France)] LV networks do not present any significant voltage problems in France. In addition, this network is not already automated. Venteea demonstrator is only focused on medium voltage network. For ERDF their main objective related to LV network is first to improve its voltage monitoring, using the new generation of secondary substations (including more sensors at this level). If a voltage constraint is detected, different smart grids solutions are under test on the French demonstrators, as for example the installation of a OLTC transformer, or the distributed voltage control at the DG level. Centralised solutions are not realistic for ERDF from an economical and a technical point of view. It is important to note for the OLTC requirements on the secondary substations are the need of additional space for the OLTC in SS and also the need of a robust MV grid because the OLTC could move the voltage constrain from LV network to the MV network. [SAG & NETZÖO (Austria)] The estimated low relevance in average seems to be based on fewer problems in LV network in most of countries covered by IGREENGrid. As in Austria the funding of PV installations favoured very low scale roof top installation and LV feeders are rather long DSOs are focusing on LV-Grid. The voltage control OLTC based only is estimated very potentially in respect to risks because it can be applied independent from customers. But the increase of hosting capacity can be limited by heterogeneous distribution of load and generation as well as by asymmetric conditions. To detect these effects monitoring is needed, which is technologically close to field measurement solutions. Perhaps in future LV Distributed (field measurements) Voltage Control with OLTC- not or only partly including DG will become important MV Congestion Management Solutions Figure 13 includes a graphical representation of the multi-criteria evaluation carried out for the different MV Congestion Management implementations in the three considered scenarios. V /12/18 69/79

70 WP4: D4.2 Figure 13 Multi-criteria evaluation of MV Congestion Management implementations (Average values) The main conclusions drawn from the analysis are the following ones: [IBERDROLA (Spain)] IBERDROLA (Spain) considers that the solutions related to the non-firm connection contract are easily scaled and replicated if the regulatory barriers were overcome. In the case of the Use of Flexibility solutions the cost (in case of a non-proper remuneration of the service provided) makes their deployment more difficult. [ERDF (France)] ERDF is testing both solutions on the Smart Grid Vendee demonstrator. Their expectations are to put in place the non-firm connection contracts for the MV generation on the next years (before 2017). The use of the flexibility through a market mechanism (call for tenders and market platform) is also under test but they do not expect to deploy them in the next years. The distributed flexibilities can already participate on the national markets/mechanisms in France. Before to put in place a local market answering to the distribution constraints, they need to establish a strong coordination with the TSO in order to avoid the conflicts among them and to establish an optimal market framework. This situation could be possible in the future. V /12/18 70/79

71 WP4: D4.2 7 Recommendations for simulation studies and Reference Targets The work completed within Work Package 4 has been based on results and experience from the IGREENGrid demonstration projects. The objective of this work was to select the most promising solutions from the demonstration projects for further evaluation using simulation studies in Work Package 5. The selection criteria was based on: feasibility, both in terms of regulatory conditions and economic expectations; the relevance to DG integration, a first selection of the different categories of solutions based on the expected requirement for these solutions on networks throughout Europe; and an indication of the performance of the solutions using the IGREENGrid KPI results. In order to determine the most promising solutions from the demonstration projects, consideration would have to be given to the deployment potential on a European scale. Work Package 4 has concluded which solutions show the most potential based on the criteria described in Section 4. Solutions from the demonstration projects were selected based on those with the highest expectations to meet these criteria. Given that these criteria are met, the ultimate decision to invest in a certain solution will be a question of economics and would be best evaluated using a CBA. Comparison of different solutions addressing similar problems on the same network can be completed using simulation studies. From the experience of the IGREENGrid demonstration projects and comparing solutions to evaluate those with the highest deployment potential, it has become apparent that this cannot be done based on a criteria that only considers the performance aspect of the solutions as defined in the IGREENGrid KPIs. Some performance targets were proposed in Section based on the average values of the IGREENGrid KPI results that were calculated using simulation studies. This result could be used as an indication of what might be expected in terms of the performance criteria represented by the KPIs as defined in Work Package 2. Ultimately the success or the deployment potential of the selected solutions would have to be determined using an approach that represents how investment decisions are made. This would include medium to long term network planning and a cost-benefit analysis. The performance of a given solution on other networks would have to be determined using simulation studies. It will then be determined if this is a successful solution, based on the performance providing the level of benefits that would have to be realised to provide a positive cost-benefit analysis. The targets for selecting the most promising solutions in WP5 would be based on comparing different solutions and determining the most economical option. To consider the deployment of a new technology (SUT), the overarching objective would be to achieve investment and operational costs over a given time horizon (planning period) that are lower than what would be expected from using traditional network reinforcements (BaU). Average values from the calculated IGREENGrid KPIs for some of the solutions are available and presented in Section However, given that performance of each solution will vary depending where it is deployed, it was decided that it would not be prudent to publish these values as V /12/18 71/79

72 WP4: D4.2 performance targets that would represent a high deployment potential. This is because these results only represent one aspect that would be considered to determine the deployment potential. The resulting values of the calculated KPIs are also a representation of the performance of the specific network and not a true representation of what should be expected from a given solution when implemented in a different network or a different part of the same network. Ultimately, the solution would have to perform sufficiently to provide a more economical option than what would be achieved without the solution. Since the relationship between the economical benefits and performance, as represented by the KPIs, is not linear and is very much dependent on where the solution is deployed, it would be misleading to provide targets based on technical performance alone. One of the main conclusions from the evaluations completed in Work Package 4 was that the benefits of different solutions, being deployed on different networks would have to be determined on a case by case basis. It is not possible to scale up results related to technical performance or economic benefits simply based on the results of a large scale demonstration project. The main outcome of Work Package 4 has been to identify the solutions that could provide the most potential based on those which are the most feasible and those that were considered to be the most relevant for DG integration on a European scale. The simulation studies in Work Package 5 could be used to validate these expectations by identifying, from a range of sample networks, where opportunities exist for realising benefits from the deployment of the implementation solutions selected in Work Package 4. Further evaluation of what benefits can be realised, compared to BaU and the implementation of different solutions selected in Work Package 4 could be based on a CBA. The evaluation could be completed using a range of sample network data that has been provided by the IGREENGrid DSO partners. The problems to be addressed on the network to facilitate DG integration will define the performance requirements. The ability of a solution to meet these performance requirements will determine which solutions should be considered. Solutions that are identified as the most promising could be those which are selected in the most number of cases to address the problems identified. The most promising solutions would also provide the greatest benefits compared to other solutions addressing the same problem and the BaU approach. The outcome of this evaluation would inevitably be dependent of the range of networks that are used. For the purpose of evaluating the European-wide potential, a range of sample networks could be used. However from experience so far both within Work Package 4 and Work Package 5, we conclude that it would be unrealistic to expect to achieve a limited number of representative networks by clustering of LV and MV networks. Network data has been provided by the IGREENGrid DSO partners. This will provide the opportunity to evaluate the deployment potential of the solutions being developed on a range of different networks. It will also be possible to compare the benefits of deploying different solutions to address the same problem on the same network. Given the uncertainty associated with predicting long term load forecasts and the uncertainty over the expected levels of DG penetration, this evaluation could also be completed for a range of different load and generation scenarios in order to provide a sensitivity analysis. For the networks considered, there were two limitations that were identified as being the first problems to be addressed to facilitate DG integration, these were described as follows. V /12/18 72/79

73 WP4: D4.2 a) Voltage constrained network: As a result of connecting DG, it is not possible to operate the network without exceeding the voltage limits (usually as defined in EN50160) under certain load and generation scenarios. b) Current constrained network: As a result of connecting DG, it is not possible to operate the network without exceeding the current limits under certain load and generation scenarios. These limits are determined by the thermal ratings of feeders, transformers etc.. If we are only considering a change to the level of DG generation on the network, then it would be sufficient to only consider the nominal network configuration. However, depending on the approach that is used (and if the evolution of the system is considered, including future load profiles, then it would also be necessary to consider contingency configuration to ensure that the security of supply requirements are met. Although this is not a problem caused by the DG it will influence the outcome of evaluating the deployment potential of the solution for DG integration. Within Work Package 5, the networks that will benefit from Voltage control or Congestion management solutions will be determined by whether they are considered as voltage or current constrained. It would also be possible to evaluate the maximum potential that could be expected from deploying a solution based on the network constraints that are not influenced by the solution. For example, the maximum performance in terms of the DG Hosting Capacity KPI, of a voltage control solution that is deployed to a network that is voltage constrained, could be determined by the current constraints of that network. The maximum potential of a solution could be calculated using simulation studies and this evaluation could help identify networks where the potential benefits from the deployment of a solution are greatest. This example also demonstrates how the benefits that are achieved from the deployment of a solution are influenced very much by where the solution is deployed and not just by the solution itself. When considering DG hosting capacity, the maximum performance of a solution could be determined by the network constraints and not only the capabilities of the solution itself. As previously explained and reflected in the results of the Preliminary evaluation described in Section 3.2, the majority of networks within the IGREENGrid demonstration projects are within rural areas and these are typically characterised by relatively lightly loaded networks with the potential for high levels of DG and usually relatively long feeders. Under these conditions, it is expected, that for most cases these networks will be what is described as voltage constrained and hence, voltage control solutions would be considered to increase the DG hosting capacity and facilitate DG integration. For both MV and LV networks, voltage regulation using reactive power control of the DG inverter was amongst the most popular. Simulation studies could be used to not just identify where opportunities for these solutions exist and evaluating the benefits, but also to investigate the expandability and limitations of a solution. The effects of implementing solutions on different types of networks, in terms of both network topology and different X/R ratio of overhead lines and underground cables, should also be explored. This would be particularly relevant for voltage control solutions using reactive power control, since the performance would be dependent on the X/R ratio of the overhead lines and V /12/18 73/79

74 WP4: D4.2 underground cables. This is of particular interest since the high R to X ratio of the underground cables would reduce the effectiveness of voltage control solutions using reactive power compensation. Generally, a larger R/X ratio would be expected in distribution networks as a result the relatively high proportion of cables used in distribution networks, compared to transmission networks. There is also drive towards cables replacing overhead lines on distribution networks due to restrictions and difficulties in building new overhead lines. This trend and the long term effectiveness of the solutions should be considered when evaluating the deployment potential. Verification of the impact on performance of voltage control solutions using reactive power control with varying X/R ratios should be completed using simulation studies within Work package 5. Another consideration for reactive power control solutions would be limits on the minimum acceptable power factor. A local or regional solution to balance the reactive power at the supplying station from TSO is required. This could require some capacitor banks and coils, SVC or STATCOM or depending on regulatory framework or a requirement for DG. An approach for Work Package 5 could be to use a sensitivity analysis where limitations are identified, considering the deployment of an alternative solution. For the case of DG VAR control, an alternative solution could be using active power control of the DG. Questions that could be answered using the simulation studies would be included, how much curtailment is needed as a percentage of total generation potential and what cost benefits could be realised from curtailment compared to other solutions such as Lithium-Ion storage or BaU. V /12/18 74/79

75 WP4: D4.2 8 Conclusions Solutions addressing voltage profile problems that are caused by new DG connections were considered to be a priority for both LV and MV networks. This conclusion is based on the experience gained from the IGREENGrid demonstration projects which mainly consist of networks in rural areas. Rural networks are usually characterised by long feeders which are lightly loaded and with the potential for relatively high levels of generation with respect to the load. It is worth mentioning that the typical characteristics of an urban distribution network, or a network supplying large industrial areas would be expected to be quite different. These networks would usually have a higher load relative to the potential generation from DG and would most likely have shorter feeders. In these cases, the first bottle neck for integrating DG would most likely be a problems caused by network congestion. An important observation from the demonstration projects within IGREENGrid would be that, unlike telecommunication systems, when it comes to electrical power systems and distribution networks, there are no two systems are alike. Consequently there is a non-linear relationship between economic investment and performance and scale and size. It also means that the performance of the distribution system, that is achieved by the deployment of a given solution, will not be the same when applied to a different network, or even different parts of the same network. When we consider the performance, such as the hosting capacity of DG as represented in one of the IGREENGrid KPIs, we are really measuring the performance of the distribution system. Although the deployment of a solution (SUT or BaU) will contribute towards the system performance, the measured or calculated performance results are an aggregation in which the characteristics of the network also play a significant role. Fundamentally, every network will have different characteristics resulting from differences in network topology, overhead line, underground cable make up of the feeders and different feeder lengths. None of these parameters are standard or related to the amount of load or generation connected to the network. This results in impedance profiles that are unique to every network. It is also true that each network has its own unique set of requirements to supply loads and, more recently, to transport energy generated at distribution level. Some of these loads and generators will be connected in close proximity to each other and close to the substations that supply them, while others will be in remote locations, connected large distances apart. The most effective way of addressing problems caused by DG would therefore be to have a range of different types of solutions that can be applied to address the different types of problems that could arise from DG integration. Given that certain technical requirements, regulatory requirements and standardisation requirements are met, it could be possible to recommend a set of solutions that could be considered to improve the cost effectiveness of DG integration. The major economical benefits, hence the driver for investment, would be from either avoiding or deferring the requirement to reinforce the network with new or upgraded cables and substations, etc. (commonly referred to as BaU). The best way to consider a list of recommended solutions would be as options that can be used. Ultimately the best way to invest in developing the network would be by considering the medium to long term evolution of the system, this would include the expectations to integrate DG, then planning the network and using a CBA to evaluate the most cost effective solutions to deploy. The best solution could indeed be a combination of deploying new technologies, such as those demonstrated in the IGREENGrid demonstration projects, and BaU. V /12/18 75/79

76 WP4: D4.2 In order to provide a list of most promising solutions, or those that are most scalable and replicable on a national and European scale we considered which solutions would be expected to be the ones that are most frequently selected to develop the system with increasing DG penetration as an integral part of the system evolution. The solutions selected were also those which were determined to be the most feasible for large scale deployment on a European scale. The feasibility for deployment was evaluated by considering technical, economic, standardisation and regulatory requirements, social aspects, reliability and the technical complexity of the solutions. Within this work package we have based our evaluation on the results and experience from the demonstration projects and using the shared experiences of the DSO partners. Although there are results from the demonstration projects and the calculated KPI results, the conclusion from the evaluations that were completed within this work package are also based on expectations. These expectations include how well solutions from one demonstration project will perform on another network, what opportunities will be available and what economic benefits can be expected. Recommendations to validate these expectations using simulation studies were provided and will be used for Work Package 5. Other expectations based on future regulatory conditions, market frameworks, standardisation requirements and the cost of new technologies will be translated into recommendations that will be shared with the relevant stakeholders in reports that will be produced within Work Package 6. In order to facilitate DG integration and address the voltage profile problems caused by increased levels of generation on distribution networks, the first place to start would be to better understand the network and to optimise the planning of new DG connections to utilise the networks existing capabilities. This is particularly relevant for LV networks which are generally not as well monitored as MV networks. The experience gained from the demonstration projects has identified opportunities where substantial benefits could be realised by improving the utilisation of the LV network though improved monitoring and network planning. By using the existing AMI with meters capable of capturing voltage measurement data, connections of rooftop PV panels could be better planned and connected to the most optimal phase. Of course this is only possible for LV networks that have three phase connections to domestic properties. However, by planning the connection of new PV panels, potential cost savings could be realised by avoiding reinforcements or investment into other solutions that would be needed to address phase to phase imbalance leading to voltage violations. In theory, knowledge of the networks existing capabilities could potentially be used to shape the growth of DG, which is directly influenced by government incentive schemes. Cost savings could be realised by utilising the existing capabilities of the network and reducing the need for network reinforcements or the need to invest in new technologies for controlling the network. Also, a more gradual and constant rate of increase of DG on distribution networks would also allow the DSOs to better plan the evolution of the distribution systems to optimise the benefits from investments that are needed to provide the increased levels of flexibility that are needed for DG integration. On medium voltage networks, voltage control solutions using both distributed and centralised control could be considered to address what is considered to be the first bottle neck for integrating DG on rural distribution networks. The most sensible approach would be to first try to address the problem using the OLTC and where it is no longer possible to maintain the voltage within the statutory limits other solutions (SUT) could be considered and compared to BAU using a CBA. V /12/18 76/79

77 WP4: D4.2 The AVR voltage control solution offers a different approach than that applied by other DSOs within the IGREENGrid project. This approach considers that ultimately network reinforcements will be required for addressing most problems associated with voltage profile and network congestion caused by DG. The application of novel solutions, such as the AVR, with a distributed control system, is designed to be a temporary solution that can provide cost savings by deferring network reinforcements. It is considered that once the network has been reinforced, there will no longer be a requirement for the voltage control solutions. The AVR is designed to be transportable to different locations on the network so it can be reused as required. The approach for addressing voltage profile problems within all the other demonstration projects is based on the permanent implementation of novel technologies and ICT. These two different approaches could be compared by considering the evolution of several networks over a given time horizon. In order to be considered, the deployment of the solutions must be feasible and ultimately an evaluation for selecting the best solution would be based on a CBA. The use of non firm grid connection contracts was considered to offer the highest deployment potential for addressing network congestion on MV networks, as a result of DG integration, in the short to medium term. Currently participation is based on a voluntary basis and regulation change would be needed to reduce the uncertainty over the potential benefits of these solutions. Other solutions implementing Lithium-Ion storage, as demonstrated in several of the IGREENGrid demonstration projects would need to reach a higher level of maturity in terms of regulatory conditions, market frameworks and cost of technology before they could be considered as a feasible option for large scale deployment and an economically viable solution for addressing DG integration. For LV networks in the majority of European countries, DG connection contracts are often defined with a fit and forget approach and active power curtailment is not allowed. In addition, the use of flexibility needs to define an appropriate market framework and an appropriate regulation framework in order to define how the DSO will cover its costs arising from the economic compensation to be paid to the aggregators for the services provided. It was concluded that the use of non firm contracts could offer potential for addressing network congestion on LV networks but the solutions are not enough mature yet to be considered for large scale deployment in the short to medium term. Developing infrastructures such as AMI for network monitoring and implementing appropriate markets and regulatory frameworks would be a prerequisite for these solutions to be practically feasible. The description of solutions presented for the Qualitative evaluation, described in Section 3.3.1, is a high level generalisation of the solutions implemented within the IGREENGrid demonstration projects and beyond. Although this generalisation of solutions was necessary for completing the evaluation, this approach proved to be more challenging than expected. It is recognised that a more structured approach, that includes all aspects, including maturity levels, would be required. It would therefore be recommended that any future work is based on a more structured approach that considers all relevant aspects. An approach for describing Smart Grid solutions is currently being developed within the DISCERN project, using maturity levels and the SGAM (Smart Grid Architecture Model). From the experience of the IGREENGrid demonstration projects and comparing solutions to V /12/18 77/79

78 WP4: D4.2 evaluate those with the greatest deployment potential, it has become apparent that this cannot be done based on a criteria that only considers the performance aspect of the solutions as defined in the IGREENGrid KPIs. Some performance targets were proposed in Section based on the average values of the IGREENGrid KPI results that were calculated using simulation studies. This result could be used as an indication of what might be expected in terms of the performance criteria represented by the KPIs as defined in Work Package 2. It was not possible to reach an overall conclusion from the SRA that was applied to the solutions selected from the demonstration projects. All implementations represent valid alternatives and the final selection by each DSO will depend on several factors such as the current status of their networks regarding the levels of monitoring and control; the past, current and future regulatory conditions in his country; DSO s approach as well as the economic implications. The results and recommendations from this Work Package are mainly focussed on the feasibility of deployment, ultimately the success or the deployment potential of the selected solutions would have to be determined using an approach that represents how investment decisions are made. This would include medium to long term network planning and a cost-benefit analysis. V /12/18 78/79

79 WP4: D4.2 9 Annexes The D4.2 Annexes are provided as a separate document _WP4_D4.2_ANNEX_v0.2.doc. The calculation procedure for the KPIs are provided in a separate project document IGREENGrid KPIs Report 10 References 10.1 Project Documents List of reference document produced in the project or part of the grant agreement [DOW] Description of Work [GA] Grant Agreement [CA] Consortium Agreement 10.2 External documents [1] EEGI Roadmap is for 2013 to 2022 which is publically available and can be downloaded from V /12/18 79/79

80 List of reference targets (countryspecific & EU-wide) for grid integration of DER This project has received funding from the European Union s Seventh Framework Programme for research, technological development and demonstration under grant agreement no

81 ID & Title : D4.2 Annex (List of reference targets (country-specific & EUwide) for grid integration of Number of pages : 126 DER) Short Description (Max. 50 words): This document contains the Annex sections for the deliverable D4.2 Version Date Modifications nature Author V0.3 18/12/2015 Accessibility: PU, Public Changes over document content and contributions integration PP, Restricted to other program participants (including the Commission Services) Gareth Bissell RE, Restricted to other a group specified by the consortium (including the Commission Services) CO, Confidential, only for members of the consortium (including the Commission Services) If restricted, please specify here the group: Owner / Main responsible: ENEL Reviewed by: RSE V4.2 ANNEX 2015/12/18 2/126

82 Authors Version Date Modifications nature Author name (s) Company V /06/17 Initialization V /11/17 Document content V /12/4 V /12/18 Changes over document content and contributions integration Changes over document content and contributions integration G. Bissell M. Rossi N. Ruiz J. Varela/D. Rubio G. Bissell M. Rossi N. Ruiz/J. Oyarzabal D. Rubio/J. Varela M. Sebastián-Viana E. Álvarez/F. Salazar C. Calpe/J. Reidick/M. Storp R. Priewasser A. Abart/E. Traxler M. Kouveletsou B. Benoit A. Dimeas / D. Koukoula/ E. Karfopoulos G. Bissell N. Ruiz D. Rubio/J. Varela M. Sebastián-Viana C. Calpe/J. Reidick/M. Storp G. Bissell N. Ruiz M. Sebastián-Viana E. Álvarez/F. Salazar ENEL RSE TECNALIA, IBERDROLA ENEL RSE TECNALIA IBERDROLA ERDF GNF RWE SAG EAG HEDNO AIT ICCS-NTUA ENEL TECNALIA IBERDROLA ERDF RWE ENEL TECNALIA ERDF GNF V4.2 ANNEX 2015/12/18 3/126

83 Table of contents AUTHORS... 3 TABLE OF CONTENTS... 4 LIST OF FIGURES & TABLES NOTATIONS, ABBREVIATIONS AND ACRONYMS ANNEX A: PRELIMINARY EVALUATION SURVEY QUESTIONNAIRE ANNEX B: DETAILED EVALUATION RESULTS MV Voltage Monitoring Performance Social Aspects Scalability and Replicability Reliability Risk on Investment Technical Complexity Technical Requirements Regulatory and Market Requirements Economical Requirements LV Voltage Monitoring Performance Social Aspects Scalability and Replicability Reliability Risk on Investment Technical Complexity Technical Requirements Regulatory and Market Requirements Economical Requirements MV Voltage Control Performance Social Aspects Scalability and Replicability Reliability Risk on Investment V4.2 ANNEX 2015/12/18 4/126

84 3.3.6 Technical Complexity Technical Requirements Regulatory and Market Requirements Economical Requirements LV Voltage Control Performance Social Aspects Scalability and Replicability Reliability Risk on Investment Technical Complexity Technical Requirements Regulatory and Market Requirements Economical Requirements MV Congestion Management Performance Social Aspects Scalability and Replicability Reliability Risk on Investment Technical Complexity Technical Requirements Regulatory and Market Requirements Economical Requirements LV Congestion Management Performance Social Aspects Scalability and Replicability Reliability Risk on Investment Technical Complexity Technical Requirements Regulatory and Market Requirements Economical Requirements V4.2 ANNEX 2015/12/18 5/126

85 4 ANNEX C: SRA SOLUTIONS DESCRIPTION MV Voltage Monitoring implementations LV Voltage Monitoring implementations MV Voltage Control implementations LV Voltage Control implementations MV Congestion Management implementations ANNEX D: SRA DATA COLLECTION ERDF (France) IBERDROLA (Spain) GNF (Spain) SAG & NETZOÖ(Austria) ENEL (Italy) RWE (Germany) HEDNO (Greece) ANNEX E: SRA RESULTS SRA for MV Voltage Monitoring implementations Description of implementations Assessment of the implementations SRA for LV Voltage Monitoring implementations Description of the implementations Assessment of the implementations SRA for MV Voltage Control implementations Description of the implementations Assessment of the implementations SRA for LV Voltage Control implementations Description of the implementations Assessment of the implementations SRA for MV Congestion Management implementations Description of the implementations Assessment of the implementations REFERENCES Project Documents External documents V4.2 ANNEX 2015/12/18 6/126

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87 List of figures & tables Figure 1 Relevance assessment for MV Voltage Monitoring (per DSO) Figure 2 Assets assessment for MV Voltage Monitoring (per DSO) Figure 3 Requirements assessment for MV Voltage Monitoring (per DSO) Figure 4 Economy assessment for MV Voltage Monitoring (per DSO) Figure 5 Risks assessment for MV Voltage Monitoring (per DSO) Figure 7 Relevance assessment for LV Voltage Monitoring (per DSO) Figure 8 Assets assessment for LV Voltage Monitoring (per DSO) Figure 9 Requirements assessment for LV Voltage Monitoring (per DSO) Figure 10 Economy assessment for LV Voltage Monitoring (per DSO) Figure 11 Risks assessment for LV Voltage Monitoring (per DSO) Figure 13 Relevance assessment for MV Voltage Control (per DSO) Figure 14 Assets assessment for MV Voltage Control (per DSO) Figure 15 Requirements assessment for MV Voltage Control (per DSO) Figure 16 Economy assessment for MV Voltage Control (per DSO) Figure 17 Risks assessment for MV Voltage Control (per DSO) Figure 19 Relevance assessment for LV Voltage Control (per DSO) Figure 20 Assets assessment for LV Voltage Control (per DSO) Figure 21 Requirements assessment for LV Voltage Control (per DSO) Figure 22 Economy assessment for LV Voltage Control (per DSO) Figure 23 Risks assessment for LV Voltage Control (per DSO) Figure 25 Relevance assessment for MV Congestion Management (per DSO) Figure 26 Assets assessment for MV Congestion Management (per DSO) Figure 27 Requirements assessment for MV Congestion Management (per DSO) Figure 28 Economy assessment for MV Congestion Management (per DSO) 124 Figure 29 Risks assessment for MV Congestion Management (per DSO) Table 1 (Acronyms) Table 2 Evaluated impact of performance on deployment potential for MV voltage monitoring solutions Table 3 Evaluated impact of social aspects on deployment potential for MV voltage monitoring solutions Table 4 Evaluated impact of scalability and replicability on deployment potential for MV voltage monitoring solutions Table 5 Evaluated impact of reliability on deployment potential for MV voltage monitoring solutions Table 6 Evaluated impact of risk on investment on deployment potential for MV voltage monitoring solutions Table 7 Evaluated impact of technical complexity on deployment potential for MV voltage monitoring solutions Table 8 Evaluated impact of technical requirements on deployment potential for MV voltage monitoring solutions V4.2 ANNEX 2015/12/18 8/126

88 Table 9 Evaluated impact of regulatory requirements on deployment potential for MV voltage monitoring solutions Table 10 Evaluated impact of economical requirements on deployment potential for MV voltage monitoring solutions Table 11 Evaluated impact of performance on deployment potential for LV voltage monitoring solutions Table 12 Evaluated impact of social aspects on deployment potential for LV voltage monitoring solutions Table 13 Evaluated impact of scalability and replicability on deployment potential for LV voltage monitoring solutions Table 14 Evaluated impact of reliability on deployment potential for LV voltage monitoring solutions Table 15 Evaluated impact of risk on investment on deployment potential for LV voltage monitoring solutions Table 16 Evaluated impact of technical complexity on deployment potential for LV voltage monitoring solutions Table 17 Evaluated impact of technical requirements on deployment potential for LV voltage monitoring solutions Table 18 Evaluated impact of regulatory requirements on deployment potential for LV voltage monitoring solutions Table 19 Evaluated impact of economical requirements on deployment potential for LV voltage monitoring solutions Table 20 Evaluated impact of performance on deployment potential for MV voltage control solutions Table 21 Evaluated impact of social aspects on deployment potential for MV voltage control solutions Table 22 Evaluated impact of scalability and replicability on deployment potential for MV voltage control solutions Table 23 Evaluated impact of reliability on deployment potential for MV voltage control solutions Table 24 Evaluated impact of risk on investment on deployment potential for MV voltage control solutions Table 25 Evaluated impact of technical complexity on deployment potential for MV voltage control solutions Table 26 Evaluated impact of technical requirements on deployment potential for MV voltage control solutions Table 27 Evaluated impact of regulatory requirements on deployment potential for MV voltage control solutions Table 28 Evaluated impact of economical requirements on deployment potential for MV voltage control solutions Table 29 Evaluated impact of performance on deployment potential for LV voltage control solutions Table 30 Evaluated impact of social aspects on deployment potential for LV voltage control solutions Table 31 Evaluated impact of scalability and replicability on deployment potential for LV voltage control solutions V4.2 ANNEX 2015/12/18 9/126

89 Table 32 Evaluated impact of reliability on deployment potential for LV voltage control solutions Table 33 Evaluated impact of risk on investment on deployment potential for LV voltage control solutions Table 34 Evaluated impact of technical complexity on deployment potential for LV voltage control solutions Table 35 Evaluated impact of technical requirements on deployment potential for LV voltage control solutions Table 36 Evaluated impact of regulatory requirements on deployment potential for LV voltage control solutions Table 37 Evaluated impact of economical requirements on deployment potential for LV voltage control solutions Table 38 Evaluated impact of performance on deployment potential for MV congestion management solutions Table 39 Evaluated impact of social aspects on deployment potential for MV congestion management solutions Table 40 Evaluated impact of scalability and replicability on deployment potential for MV congestion management solutions Table 41 Evaluated impact of reliability on deployment potential for MV congestion management solutions Table 42 Evaluated impact of risk on investment on deployment potential for MV congestion management solutions Table 43 Evaluated impact of technical complexity on deployment potential for MV congestion management solutions Table 44 Evaluated impact of technical requirements on deployment potential for MV congestion management solutions Table 45 Evaluated impact of regulatory requirements on deployment potential for MV congestion management solutions Table 46 Evaluated impact of economical requirements on deployment potential for MV congestion management solutions Table 47 Evaluated impact of performance on deployment potential for LV congestion management solutions Table 48 Evaluated impact of social aspects on deployment potential for LV congestion management solutions Table 49 Evaluated impact of scalability and replicability on deployment potential for LV congestion management solutions Table 50 Evaluated impact of reliability on deployment potential for LV congestion management solutions Table 51 Evaluated impact of risk on investment on deployment potential for LV congestion management solutions Table 52 Evaluated impact of technical complexity on deployment potential for LV congestion management solutions Table 53 Evaluated impact of technical requirements on deployment potential for LV congestion management solutions Table 54 Evaluated impact of regulatory requirements on deployment potential for LV congestion management solutions V4.2 ANNEX 2015/12/18 10/126

90 Table 55 Evaluated impact of economical requirements on deployment potential for LV congestion management solutions Table 56 MV Voltage Monitoring (field measurement) description Table 57 MV Voltage Monitoring (SE) description Table 58 MV Voltage Monitoring (PLF) description Table 59 LV Supervised Voltage Control (AMI) description Table 60 MV Distributed Voltage Control with OLTC description Table 61 MV Distributed Voltage Control with OLTC, DG description Table 62 MV Centralised (field measurements) Voltage Control with OLTC description Table 63 MV Supervised (field measurements) Voltage Control with OLTC & DG description Table 64 MV Supervised Voltage Control with OLTC & DG description Table 65 MV Centralized (SE) Voltage Control with OLTC description Table 66 MV Centralised (SE & OPF) Voltage Control with OLTC & DG description Table 67 LV Distributed Voltage Control with OLTC description Table 68 LV Distributed Voltage Control with DG description Table 69 LV Distributed Voltage Control with OLTC, DG description Table 70 LV Distributed (field measurements) Voltage Control with OLTC, DG description Table 71 MV Congestion Management with DG non-firm grid connection contracts description Table 72 MV Congestion Management with DG non-firm grid connection contracts Table 73 List of surveyed DSOs Table 74 Functionalities considered for the SRA Table 75 SRA data for ERDF (France) Scenario: Scalability in density Table 76 SRA data for ERDF (France) Scenario: Replicability (Today) Table 77 SRA data for ERDF (France) Scenario: Replicability (Future) Table 78 SRA data for IBERDROLA (Spain) Scenario: Scalability in density Table 79 SRA data for IBERDROLA (Spain) Scenario: Replicability (Today) Table 80 SRA data for IBERDROLA (Spain) Scenario: Replicability (Future) Table 81 SRA data for GNF (Spain) Scenario: Scalability in density Table 82 SRA data for GNF (Spain) Scenario: Replicability (Today) Table 83 SRA data for GNF (Spain) Scenario: Replicability (Future) Table 84 SRA data for SAG & NetzOÖ (Austria) Scenario: Scalability in density Table 85 SRA data for SAG & NetzOÖ (Austria) Scenario: Replicability (Today) Table 86 SRA data for SAG & NetzOÖ (Austria) Scenario: Replicability (Future) Table 87 SRA data for ENEL (Italy) Scenario: Scalability in density Table 88 SRA data for ENEL (Italy) Scenario: Replicability (Today) Table 89 SRA data for ENEL (Italy) Scenario: Replicability (Future) Table 90 SRA data for RWE (Germany) Scenario: Scalability in density Table 91 SRA data for RWE (Germany) Scenario: Replicability (Today) V4.2 ANNEX 2015/12/18 11/126

91 Table 92 SRA data for RWE (Germany) Scenario: Replicability (Future) Table 93 SRA data for HEDNO (Greece) Scenario: Scalability in density Table 94 SRA data for HEDNO (Greece) Scenario: Replicability (Today) Table 95 SRA data for HEDNO (Greece) Scenario: Replicability (Future) Table 96 List of implementations for MV Voltage Monitoring Table 97 Relevance assessment for MV Voltage Monitoring (Average values). 87 Table 98 Assets assessment for MV Voltage Monitoring (Average values) Table 99 Requirements assessment for MV Voltage Monitoring (Average values) Table 100 Economy assessment for MV Voltage Monitoring (Average values). 92 Table 101 Risks assessment for MV Voltage Monitoring (Average) Table 102 List of implementations for LV Voltage Monitoring Table 103 Relevance assessment for LV Voltage Monitoring (Average values) 96 Table 104 Assets assessment for LV Voltage Monitoring (Average values) Table 105 Requirements assessment for LV Voltage Monitoring (Average values) Table 106 Economy assessment for LV Voltage monitoring (Average values).. 98 Table 107 Risks assessment for LV Voltage Monitoring (Average values) Table 108 List of implementations for MV Voltage Control Table 109 Relevance assessment for MV Voltage Control (Average values) Table 110 Assets assessment for the MV Voltage Control (Average values) Table 111 Requirements assessment for the MV Voltage Control (Average values) Table 112 Economy assessment for the MV Voltage Control (Average values) Table 113 Risks assessment for the MV Voltage Control (Average values) Table 114 List of implementations for LV Voltage Control Table 115 Relevance assessment for the LV Voltage Control Table 116 Assets assessment for the LV Voltage Control Table 117 Requirements assessment for the LV Voltage Control Table 118 Economy assessment for the LV Voltage Control Table 119 Risks assessment for the LV Voltage Control Table 120 List of implementations for MV Congestion Management Table 121 Relevance assessment for MV Congestion Management (Average values) Table 122 Assets assessment for MV Congestion Management (Average values) Table 123 Requirements assessment for MV Congestion Management (Average values) Table 124 Economy assessment for MV Congestion Management (Average values) Table 125 Risks assessment for MV Congestion Management (Average values) V4.2 ANNEX 2015/12/18 12/126

92 1 Notations, abbreviations and acronyms 3G ADSL AFR AGR AMI AMM AMR AOD AR ARQ BPL CB CEN CIS CO2 CPP CSMA/CA DCS DRES DLMS DMS DNA DNO DPF DSO EU FD FEC FH FTP GPRS HTTP HTTPS HV HW IEEE IHD IP 3rd generation of mobile telecommunications technology Asymmetric Digital Subscriber Line Automatic Feeder Reconfiguration Automatic Grid Recovery Advanced Metering Infrastructure Automatic Meter Management Automatic Meter Reading Automatic Outage Detection Automatic Restoration Automatic Repeat-reQuest Broadband power line Circuit Breaker Customer Engagement Customer Information System Carbon Dioxide Critical Peak Pricing Carrier Sense Multiple Access with Collision Avoidance Distribution Control System Distributed Renewable Energy Sources Device Language Message Specification Distributed Management System Distribution Network Applications Distribution Network Operator Dispatching Power Flow Distribution System Operator European Union Fault Detector Forward Error Correction Feeder Head File Transfer Protocol General Packet Radio Service Hypertext Transfer Protocol Hypertext Transfer Protocol Secure High Voltage Hardware Institute of Electrical and Electronics Engineers In Home Display Internet Protocol V4.2 ANNEX 2015/12/18 13/126

93 IPSEC KPI LDAP LED LV MAC MDC MMI MV OFDM OH PC PHY PLC PLC PRIME QoS RMS RTU SCADA SEV SIC SFD SGAM SGCG SOAP SS SSL SSN STG SW TCP THD TLS TM TOU TSO VDU VHF VSAT WAN WS xdsl XML Internet Protocol Security Key performance indicator Lightweight Directory Access Protocol Light Emitting Diode Low Voltage Media Access Control Meter Data Collector Man-Machine Interface Medium Voltage Orthogonal Frequency-Division Multiplexing Over Head Project Coordinator Abbreviation for the physical layer of the OSI model Power Line Communication Programmable Logic Controller Standard definition narrow-band Power Line Communication Quality of Service Root Mean Square Remote Terminal Unit Supervisory Control And Data Acquisition It's a unicast, multicast or broadcast packet to send a synchronous event from a Node of a Subnetwork to another Node of the same Subnetwork Customer Information System Standalone Fault Detector Smart Grid Architecture Model Smart Grid Coordination Group Simple Object Access Protocol Secondary Substation Secure Socket Layer Secondary Substation Node Remote Management System (LV measurements centralized collection) Software Transmission Control Protocol Total Harmonic Distortion Transport Layer Security Technical Manager Time-of-Use Transmission System Operator Visual Display Unit Very High Frequency Very-Small-Aperture Terminal Wide Area Network Web Services Digital Subscriber Line technologies extensible Markup Language V4.2 ANNEX 2015/12/18 14/126

94 ZigBee Specification for a suite of high level communication protocols using small, low-power digital radios based on an IEEE 802 standard for personal area networks Table 1 (Acronyms) V4.2 ANNEX 2015/12/18 15/126

95 2 Annex A: Preliminary Evaluation Survey Questionnaire This preliminary evaluation has been made using a questionnaire which was sent to each DSO to complete for each Use Case within their demonstration project. A template for this survey questionnaire is given below: V4.2 ANNEX 2015/12/18 16/126

96 Project name: Use Case: IGREENGrid Reference Please complete the following questions by selecting the most applicable response. The objective of this survey is to provide a high level assessment for each of the criteria and will be used to complete the preliminary evaluation as part of WP4 of the IGREENGrid project. To reduce ambiguity some examples are given to provide a guide to the categorisation for each question. These examples are only intended as a guide so please feel free adapt and make your evaluation with justification in the comments section provided. (Please select one category for each question by inserting an X ) 1. To what extent could a large scale deployment of the solution be used to address expected problems on your network(s)? LOW Comments (obligatory: please provide justification similar to the examples provided ) 2. What level of investment was needed to implement the solution in the demo? Problem that is being addressed by the solution in demo is wide spread throughout network that would require substantial investment in network reinforcements (e.g. A high percentage of investment for next 10 years) Problems on the network have been identified for certain parts of the network but relative investment needed to address these problems is medium to low (e.g. A reasonable percentage of investment for next 10 years) Similar problems on network are possible but not yet identified or are present on a small scale (e.g. A low percentage of investment for next 10 years) Equivalent to major reinforcement costs (e.g. new line / new substations) Equivalent to moderate reinforcement costs (Upgrading switch gear / protection system) Relatively low cost compared to reinforcing the network (less than upgrading switch gear / protection system) 3. What are the expected benefits of the solution? (not restricted to the demo project) Expected potential to defer major reinforcements to the network (e.g. new lines / upgrading or new substations etc.) Could help to reduce total investment costs on network for forecast integration of RES Highest economical benefits expected are by improving performance of network and hence operational costs (e.g. reliability, customer satisfaction) but no savings in capital expenditure can be identified 4. Are the objectives supported by results? Yes, most objectives of the project have been achieved and are supported by result from the demo Yes partially, some of the objectives have been achieved and are supported by results from the demo No, objectives have either not been achieved or the results are not yet available from the demo project 5. What is your expectation of the level of potential risk associated with the successful large scale deployment (on a European scale) of the solutions you are testing in the demo? Successful deployment of the solution being tested in the demo is dependent on existing infrastructure (e.g. communications, ICT or smart meters) and substantial investment would be needed if this did not exist that could impact the economical justification for deployment of the solution (i.e. it could be more economical to reinforce the network using new lines, upgrading substations etc.) Regulatory conditions (e.g. ability for DSO to control injected power from PV at PCC) or standardisation issues requiring substantial costs would have to be resolved for successful deployment of the solution outside the demo No issues have been identified where regulatory conditions (existing conditions) or standardisation of technologies used that could have an impact on the economical / practicality of a large scale (European) deployment V4.2 ANNEX 2015/12/18 17/126

97 3 Annex B: Detailed Evaluation Results The solutions identified from the preliminary evaluation were further evaluated based on the concepts described in Section 4 of the deliverable D4.2 and a rating was given for the expected deployment potential. The results, along with a justification for the allocated deployment potential are presented here for each implementation category. 3.1 MV Voltage Monitoring Performance Deployment potential MV Voltage Monitoring (PLF) MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) Table 2 Evaluated impact of performance on deployment potential for MV voltage monitoring solutions The highest performing solution for MV monitoring is the one based on State Estimator (SE). The main factor influencing this result is that SE uses quasi-real time, and that it allows the operator knowing the real estate of the grid at any moment. The advantage of the SE when compared with the use of Remote Terminal Units (RTUs), which is also able to provide real-time information, is that SE provides the added value of correcting wrong and incoherent values. SE has been considered more accurate than Probalistic Load Flow (PLF), because the last one, even working with more data (historical grid and generation information from years, months, days), it works with a low amount of sensors that provide, in the best case, data from the day before. This solution is especially useful for grids with a low degree of automation Social Aspects Deployment potential MV Voltage Monitoring (PLF) MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) Table 3 Evaluated impact of social aspects on deployment potential for MV voltage monitoring solutions All solutions are equally classified regarding social aspects, with a quite positive position with respect to society impact. The reason is that monitoring solutions do not strongly impact on customer perception. They are not conscious of the presence of this type of solutions. V /12/18 18/126

98 3.1.3 Scalability and Replicability Deployment potential MV Voltage Monitoring (PLF) MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) Table 4 Evaluated impact of scalability and replicability on deployment potential for MV voltage monitoring solutions The PLF solution is the most scalable one, because it is based totally on off-line studies, using load and generation profiles from and the existing sensors, off-line voltage measurements and Advanced Metering Infrastructure (AMI) data, whichever is available. Due to the use of historical data, it does not lay on the use of a large amount of sensors. SE and RTU solutions could be less scalable because they involve a large amount of sensors in their deployment and they work in real-time demanding new telecom infrastructure development Reliability Deployment potential MV Voltage Monitoring (PLF) MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) Table 5 Evaluated impact of reliability on deployment potential for MV voltage monitoring solutions The allocation of an overall score for the reliability of a solution was given by considering the operational impact, probability and repair time for three categories of failure. ICT Failure A high level of reliability is expected for whatever type of communications is used. From an ICT perspective the RTU could require a broadband communication system, this could be LTE from the secondary to primary substation. In some cases broadband PLC or even optical fibre could be used. The impact of an ICT failure on these solutions, which is entirely based on field measurements would degrade the functionality of the monitoring system. The extent of the impact of an ICT failure would depend on the type and location of the fault. If the communications for a single RTU is lost, then this would of course have less impact than losing the communications between the concentrator and the operation centre. Although interruptions, for a short duration it may be possible using systems such as LTE or PLC. This could be due to unavailability of the network in some remote regions or inference. These type of faults are usually quickly autonomously restored. The loss of communications for such a short duration would have little impact where monitoring is used for operation of the network. This of V /12/18 19/126

99 course would be more critical where monitoring is used as part of the solution (such as voltage control) and this will be addressed separately for those solutions. A major fault such as rupturing an optical fibre, although it is possible, it is considered to be highly unlikely. This type of failure would have a larger impact, especially if it is the communications between the concentrator at the primary substation on the control centre, and a larger restoration time. But given the low probability of this type of failure the overall reliability is considered to be high. Device failure For this solution we consider the RTU devices themselves. The technologies or application of these devices are not new to power systems and they can be considered to have a high level of reliability. Since there is no possibility of a common mode failure and failure of an individual device will degrade but not prevent the monitoring of the network, the impact of such failure is considered to be relatively low. Combined with these factors and a low to medium expectations for the fault restoration time, the overall reliability of the devices used in this solution are considered to be high. Control system failure Not relevant for this solution so therefore a high score was allocate to reflect that this parameter has no impact on the deployment potential Risk on Investment Deployment potential MV Voltage Monitoring (PLF) MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) Table 6 Evaluated impact of risk on investment on deployment potential for MV voltage monitoring solutions Limited risk on investment for all categories considered reflects a high deployment potential for all solutions Technical Complexity Deployment potential MV Voltage Monitoring (PLF) MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) Table 7 Evaluated impact of technical complexity on deployment potential for MV voltage monitoring solutions V /12/18 20/126

100 A relatively low technical complexity would be expected for all the solutions for all the categories as described in Section 4.1 of the deliverable D4.2. This would result in an expected high deployment potential Technical Requirements Deployment potential MV Voltage Monitoring (PLF) MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) LOW Table 8 Evaluated impact of technical requirements on deployment potential for MV voltage monitoring solutions We need to test the three solutions because they are used for the Voltage Control Regulatory and Market Requirements Deployment potential MV Voltage Monitoring (PLF) MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) Table 9 Evaluated impact of regulatory requirements on deployment potential for MV voltage monitoring solutions The only regulatory requirement is the right to access and use metering data (individual or concentrated) Economical Requirements Deployment potential MV Voltage Monitoring (PLF) MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) LOW LOW Table 10 Evaluated impact of economical requirements on deployment potential for MV voltage monitoring solutions A low deployment potential was assigned to the solutions using real time field measurements and the State Estimator. This is due to the large number of RTU devices required and the relative expense compared to the MV Monitoring solution using PLF. V /12/18 21/126

101 3.2 LV Voltage Monitoring Performance Deployment potential LV Voltage Monitoring (AMI) LV Voltage Monitoring (AMI+SE) LV Voltage Monitoring (RTU) LV Voltage Monitoring (SE) Table 11 Evaluated impact of performance on deployment potential for LV voltage monitoring solutions The solution with the highest performance is the SE and AMI+SE because they involve the use of real-time information, it manages a relatively large amount of information, and it has higher potential to increase the hosting capacity than the rest. Due to the high observability of the network, a more accurate planning and operation can be performed, and, moreover, the HC can be increased. The solution with the lowest performance for LV monitoring is the one based only on AMI, due to the low frequency of data acquisition from the smart meters (e.g. once a day). If in a future the update rate of information is higher it may become much more interesting, given that it provides information all along the LV lines Social Aspects Deployment potential LV Voltage Monitoring (AMI) LV Voltage Monitoring (AMI+SE) LV Voltage Monitoring (RTU) LV Voltage Monitoring (SE) Table 12 Evaluated impact of social aspects on deployment potential for LV voltage monitoring solutions The most penalized solutions in LV monitoring are the ones including AMI, basically because they have a bad perception in terms of data privacy in certain countries, while the other solutions are transparent or inexistent for the citizen. It has also been considered that the Smart Meters deployment cannot be done without explanations to the customers. V /12/18 22/126

102 3.2.3 Scalability and Replicability Deployment potential LV Voltage Monitoring (AMI) LV Voltage Monitoring (AMI+SE) LV Voltage Monitoring (RTU) LV Voltage Monitoring (SE) Table 13 Evaluated impact of scalability and replicability on deployment potential for LV voltage monitoring solutions If the solution based on AMI is going to be applied on a network that has already deployed the Smart Metering, it becomes very easy to be scaled up, given that is basically software based. If the DSO has not deployed SM yet, which is the habitual case in Europe, the implementation implies an enormous amount of equipment to be installed. Another relevant aspect is the low standardization level of these solutions. RTU solutions are at the top of the classification in terms of S&R because it is considered that in case of installing new sensors the amount of them is much lower than in the AMI case Reliability Deployment potential LV Voltage Monitoring (AMI) LV Voltage Monitoring (AMI+SE) LV Voltage Monitoring (RTU) LV Voltage Monitoring (SE) Table 14 Evaluated impact of reliability on deployment potential for LV voltage monitoring solutions The reliability of the LV monitoring solutions would be expected to be very similar to the MV voltage monitoring solution, please see explanation in Section It was noted that, due to the relative scale of LV networks, the solution using field measurements that requires the installation of RTU devices would imply the installation of many more RTUs when compared to the MV network. This would of course result in a higher probability of device failure, however the overall reliability of the system would still be considered to be high. Since the LV voltage monitoring solutions that use AMI are using the existing AMI, it is therefore a requirement and not part of the voltage monitoring solution. The reliability of the AMI is therefore not considered and for the purpose of this evaluation and the reliability of the AMI is assumed to be perfect. V /12/18 23/126

103 3.2.5 Risk on Investment Deployment potential LV Voltage Monitoring (AMI) LV Voltage Monitoring (AMI+SE) LV Voltage Monitoring (RTU) LV Voltage Monitoring (SE) Table 15 Evaluated impact of risk on investment on deployment potential for LV voltage monitoring solutions Limited risk on investment for all categories considered reflects a high deployment potential for all solutions Technical Complexity Deployment potential LV Voltage Monitoring (AMI) LV Voltage Monitoring (AMI+SE) LV Voltage Monitoring (RTU) LV Voltage Monitoring (SE) Table 16 Evaluated impact of technical complexity on deployment potential for LV voltage monitoring solutions A relatively low technical complexity would be expected for all solutions for all the categories as described in Section 4.1 of the deliverable D4.2. This would result in an expected high deployment potential Technical Requirements Deployment potential LV Voltage Monitoring (AMI) LV Voltage Monitoring (AMI+SE) LV Voltage Monitoring (RTU) LV Voltage Monitoring (SE) LOW Table 17 Evaluated impact of technical requirements on deployment potential for LV voltage monitoring solutions One of the main challenges for LV monitoring is the high rate of voltage fluctuations with respect to MV and these results in the requirement for a higher sampling rate. There is also a requirement for V /12/18 24/126

104 three phase measurements which will also increase the amount of data that has to be captured, transmitted or stored and processed. It is therefore expected that the communications bandwidth or memory storage and data processing requirements would be very high compared to similar solutions that are developed for the MV network. A good solution would be to use AMI to provide voltage profile monitoring, using statistical data to reduce bandwidth/memory /data processing requirements. A solution providing data only for relevant intervals regarding maximum & minimum or certain percentiles of voltage levels all over the LV-grid would perfectly meet the requirements in respect to network planning as well as privacy of customers (e.g. Austria Power Snapshot analysis). However, it should be noted that a voltage monitoring function are not standard for meters. Also, access to meter data could also be an issue in some countries where DSO is not responsible for metering, need to request this data. (e.g. Germany, UK), have to request each customer. They only have access to monthly consumption data Regulatory and Market Requirements Deployment potential LV Voltage Monitoring (AMI) LV Voltage Monitoring (AMI+SE) LV Voltage Monitoring (RTU) LV Voltage Monitoring (SE) Table 18 Evaluated impact of regulatory requirements on deployment potential for LV voltage monitoring solutions The only regulatory requirement is the right to access and use metering data (individual or concentrated) Economical Requirements Deployment potential LV Voltage Monitoring (AMI) LV Voltage Monitoring (AMI+SE) LV Voltage Monitoring (RTU) LV Voltage Monitoring (SE) LOW LOW LOW Table 19 Evaluated impact of economical requirements on deployment potential for LV voltage monitoring solutions V /12/18 25/126

105 For the solutions using AMI infrastructure, it is assumed that this infrastructure are already deployed on the country. In that case these solutions need only software processing existing data. The costs of these solutions are lower than the others. 3.3 MV Voltage Control Performance Deployment potential MV Centralised (field measurements) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG MV Centralised (SE & OPF) Voltage Control with OLTC & DG & STATCOM MV Centralised (SE & OPF) Voltage Control with OLTC & DG & Storage MV Centralised (SE & OPF) Voltage Control with OLTC & DG active power modulation MV Centralised (SE) Voltage Control with OLTC MV Centralised (SE) Voltage Control with OLTC & DG & Storage MV Distributed Voltage Control with AVR MV Distributed Voltage Control with DG active power modulation MV Distributed Voltage Control with Local Storage MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG LOW Table 20 Evaluated impact of performance on deployment potential for MV voltage control solutions The highest performing solutions regarding Hosting Capacity increase are the most complex ones including MV Centralized Voltage Control with OLTC, DG and an additional element like Storage, or STATCOM or these using some kind of flexibility (active power modulation,...). These systems also present State Estimation or /and OPF algorithms that complete its functionality. They include the highest degree of control, are the best option to increase the hosting capacity, and gather a high amount of information. They also have a high flexibility, understood as granularity in the control, provided by power electronics. Generally, Centralised solutions are better classified than supervised or distributed ones, and DG, STATCOM, Storage and AVR are elements that favour the solutions in terms of performance. The lowest performing solutions are the simpler ones, because they have fewer elements to react to distributed problems, and the lack of tools to improve the performance of the solution. V /12/18 26/126

106 3.3.2 Social Aspects Deployment potential MV Centralised (field measurements) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG MV Centralised (SE & OPF) Voltage Control with OLTC & DG & STATCOM MV Centralised (SE & OPF) Voltage Control with OLTC & DG & Storage MV Centralised (SE & OPF) Voltage Control with OLTC & DG active power modulation MV Centralised (SE) Voltage Control with OLTC MV Centralised (SE) Voltage Control with OLTC & DG & Storage MV Distributed Voltage Control with AVR MV Distributed Voltage Control with DG active power modulation MV Distributed Voltage Control with Local Storage MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG LOW LOW Table 21 Evaluated impact of social aspects on deployment potential for MV voltage control solutions Regarding social aspects, the classification ends with the solutions using Storage, due to environmental aspects, the need of containers to install them and the consequent explanations to users. In certain countries citizens have the perception that a battery may be the cause of an explosion in the neighbourhood. The solutions with lower impact on society are the simpler ones (the ones with only OLTC), because they do not have elements that can be perceived by the final user. V /12/18 27/126

107 3.3.3 Scalability and Replicability Deployment potential MV Centralised (field measurements) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG MV Centralised (SE & OPF) Voltage Control with OLTC & DG & STATCOM MV Centralised (SE & OPF) Voltage Control with OLTC & DG & Storage MV Centralised (SE & OPF) Voltage Control with OLTC & DG active power modulation MV Centralised (SE) Voltage Control with OLTC MV Centralised (SE) Voltage Control with OLTC & DG & Storage MV Distributed Voltage Control with AVR MV Distributed Voltage Control with DG active power modulation MV Distributed Voltage Control with Local Storage MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Supervised Voltage Control with OLTC & DG MV Supervised (field measurements) Voltage Control with OLTC & DG LOW LOW LOW LOW LOW LOW LOW LOW Table 22 Evaluated impact of scalability and replicability on deployment potential for MV voltage control solutions The Centralised Voltage control with OLTC, DG and storage solution is the least scalable, due to the need of modifying contracts, the elevated need of space, and the low standardisation of the solution and components. The most scalable ones are the implementations based exclusively on OLTC, due to its simplicity. Generally, centralised control is less scalable than distributed one, mainly because of the large amount of sensors, telecom equipment, the need of space for storage, and the need of modifying contracts. V /12/18 28/126

108 3.3.4 Reliability Deployment potential MV Centralised (field measurements) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG MV Centralised (SE & OPF) Voltage Control with OLTC & DG & STATCOM MV Centralised (SE & OPF) Voltage Control with OLTC & DG & Storage MV Centralised (SE & OPF) Voltage Control with OLTC & DG active power modulation MV Centralised (SE) Voltage Control with OLTC MV Centralised (SE) Voltage Control with OLTC & DG & Storage MV Distributed Voltage Control with AVR MV Distributed Voltage Control with DG active power modulation MV Distributed Voltage Control with Local Storage MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG Table 23 Evaluated impact of reliability on deployment potential for MV voltage control solutions As with all centralised solutions a failure of the SCADA or communication system would prevent the operation of the voltage control system. Although the impact is high, the probability of a SCADA or communications failure is very low. The SCADA and communications systems are not new technologies and there is therefore no risk of uncertainty that might be expected from using new technologies. Failure of the transformer (OLTC) would also prevent functionality of the solution, however the likelihood of such a failure is very low. Again, the OLTC transformer is nothing new at this voltage level. A long interruption time would be associated with a transformer failure however, given the low likelihood of failure, this was not considered to have an adverse impact on the overall reliability score for this solution. The Lithium Ion storage facility is a new technology and, at least for the near future, a slightly lower reliability could be expected when compared to other technologies that have been used on the grid for many years. The impact on the voltage control functionality of losing the storage facility depends on to what extent the storage facility is needed to maintain the required voltage profile. Factors that will influence this include the generation / load profile on the network. This would be determined by the amount of DRES connected to the network and the time or year or time of day V /12/18 29/126

109 when the failure occurs. In this solution we have other devices that could still contribute to maintaining the voltage profile in the event of a failure of the storage facility Risk on Investment Deployment potential MV Centralised (field measurements) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG MV Centralised (SE & OPF) Voltage Control with OLTC & DG & STATCOM MV Centralised (SE & OPF) Voltage Control with OLTC & DG & Storage MV Centralised (SE & OPF) Voltage Control with OLTC & DG active power modulation MV Centralised (SE) Voltage Control with OLTC MV Centralised (SE) Voltage Control with OLTC & DG & Storage MV Distributed Voltage Control with AVR MV Distributed Voltage Control with DG active power modulation MV Distributed Voltage Control with Local Storage MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG LOW LOW LOW LOW LOW Table 24 Evaluated impact of risk on investment on deployment potential for MV voltage control solutions Low scores were given to the following solutions to indicate a high risk on investment. This is based on existing regulation, standardisation and market frameworks. Voltage control solutions using storage (Lithium ion) There is still more work to do to establish market framework and regulation for the operation of storage facilities on distribution networks. A relatively high level of risk on investment would therefore be expected until this uncertainty is resolved. Controlling DG using active power modulation Under existing regulation, it is not possible for DSOs to control either active or reactive power of DG. Within the demonstration projects, control of the DG has been achieved using bilateral contracts on a voluntary basis. This of course would present a risk to any large scale deployment of these solutions unless regulatory change would allow the DSOs to control the DG. V /12/18 30/126

110 3.3.6 Technical Complexity Deployment potential MV Centralised (field measurements) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG MV Centralised (SE & OPF) Voltage Control with OLTC & DG & STATCOM MV Centralised (SE & OPF) Voltage Control with OLTC & DG & Storage MV Centralised (SE & OPF) Voltage Control with OLTC & DG active power modulation MV Centralised (SE) Voltage Control with OLTC MV Centralised (SE) Voltage Control with OLTC & DG & Storage MV Distributed Voltage Control with AVR MV Distributed Voltage Control with DG active power modulation MV Distributed Voltage Control with Local Storage MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG LOW LOW LOW LOW Table 25 Evaluated impact of technical complexity on deployment potential for MV voltage control solutions A relatively high technical complexity would be expected for the solutions using centralised control systems. This would result in the expectation of a relatively low deployment potential. An increased technical complexity was also associated with solutions that are using new technologies such as storage where additional systems are introduced. Solutions using many components, such as field measurements (RTUs) or controlling DG (controlling the inverters) were also given a lower score for deployment potential based on the increased technical complexity. V /12/18 31/126

111 3.3.7 Technical Requirements Deployment potential MV Centralised (field measurements) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG MV Centralised (SE & OPF) Voltage Control with OLTC & DG & STATCOM MV Centralised (SE & OPF) Voltage Control with OLTC & DG & Storage MV Centralised (SE & OPF) Voltage Control with OLTC & DG active power modulation MV Centralised (SE) Voltage Control with OLTC MV Centralised (SE) Voltage Control with OLTC & DG & Storage MV Distributed Voltage Control with AVR MV Distributed Voltage Control with DG active power modulation MV Distributed Voltage Control with Local Storage MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG LOW LOW LOW LOW LOW Table 26 Evaluated impact of technical requirements on deployment potential for MV voltage control solutions Storage and STATCOM solutions are discarded because they need more technical requirements than the others. We discarded also solutions using AVR and Local storage because they are not standard devices and mere experiences are needed by the DSO before to standardize these devices. We think that the use of DG (active of reactive) on the MV Centralised (SE & OPF) Voltage Control with OLTC solution improve this solution. However from a Technical requirement point of view they have more requirements. We consider that solutions using field measurements in some critical nodes and solutions using SE should be compared in a work studying phase in order to compare the results in different scenarios (MV Centralised (SE) Voltage Control with OLTC, MV Centralised (field measurements) Voltage Control with OLTC, MV Supervised Voltage Control with OLTC & DG, MV Supervised (field measurements) and Voltage Control with OLTC & DG solutions) We consider than MV Distributed Voltage Control with OLTC and MV Distributed Voltage Control with OLTC,DG are the most promising distributed solutions from a technical requirement point of V /12/18 32/126

112 view because we want to obtain the comparison results between the use of do nothing scenario and the contribution of DG to the voltage control Regulatory and Market Requirements Deployment potential MV Centralised (field measurements) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG MV Centralised (SE & OPF) Voltage Control with OLTC & DG & STATCOM MV Centralised (SE & OPF) Voltage Control with OLTC & DG & Storage MV Centralised (SE & OPF) Voltage Control with OLTC & DG active power modulation MV Centralised (SE) Voltage Control with OLTC MV Centralised (SE) Voltage Control with OLTC & DG & Storage MV Distributed Voltage Control with AVR MV Distributed Voltage Control with DG active power modulation MV Distributed Voltage Control with Local Storage MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG LOW LOW LOW LOW LOW Table 27 Evaluated impact of regulatory requirements on deployment potential for MV voltage control solutions Additional regulatory requirement are needed in case of solutions using DG contribution. In some European countries today this contributions are not considered on the existing regulatory framework. V /12/18 33/126

113 3.3.9 Economical Requirements Deployment potential MV Centralised (field measurements) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG MV Centralised (SE & OPF) Voltage Control with OLTC & DG & STATCOM MV Centralised (SE & OPF) Voltage Control with OLTC & DG & Storage MV Centralised (SE & OPF) Voltage Control with OLTC & DG active power modulation MV Centralised (SE) Voltage Control with OLTC MV Centralised (SE) Voltage Control with OLTC & DG & Storage MV Distributed Voltage Control with AVR MV Distributed Voltage Control with DG active power modulation MV Distributed Voltage Control with Local Storage MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Supervised Voltage Control with OLTC & DG MV Supervised (field measurements) Voltage Control with OLTC & DG LOW LOW LOW LOW Table 28 Evaluated impact of economical requirements on deployment potential for MV voltage control solutions The costs depend on the number of devices used, the communication infrastructure and the retrofitting needed to put in place the solutions. V /12/18 34/126

114 3.4 LV Voltage Control Performance Deployment potential LV Centralised (SE & OPF) Voltage Control with OLTC & DG & LV Distributed (field measurements) Voltage Control with OLTC LV Distributed (field measurements) Voltage Control with OLTC, DG LV Distributed Voltage Control with AVR LV Distributed Voltage Control with DG LV Distributed Voltage Control with DG active power modulation LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with OLTC, DG LV Distributed Voltage Control with STATCOM LV Supervised (field measurements) Voltage Control with OLTC & DG LOW Table 29 Evaluated impact of performance on deployment potential for LV voltage control solutions The highest performing solutions regarding LV control are the Centralised and Supervised Voltage Control with OLTC, DG and State Estimation and OPF algorithms, because of its higher impact in terms of hosting capacity increase, the capacity to manage the highest amount of information, a high degree of control, and the possibility to coordinate a wider area. The lowest performing LV voltage control solutions would be those with only one control element, especially if it is a solution that works without coordination with other similar elements, like distributed OLTC, which is also penalised for not being applicable at any place, given that its efficacy depends on the local lines state. V /12/18 35/126

115 3.4.2 Social Aspects Deployment potential LV Centralised (SE & OPF) Voltage Control with OLTC & DG & LV Distributed (field measurements) Voltage Control with OLTC LV Distributed (field measurements) Voltage Control with OLTC, DG LV Distributed Voltage Control with AVR LV Distributed Voltage Control with DG LV Distributed Voltage Control with DG active power modulation LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with OLTC, DG LV Distributed Voltage Control with STATCOM LV Supervised (field measurements) Voltage Control with OLTC & DG Table 30 Evaluated impact of social aspects on deployment potential for LV voltage control solutions The criteria for LV control solutions are the same as for MV ones. The ones with only OLTC are best classified, with no impact on customers, and the ones that have more impact on society are the Distributed control with DG -active power modulation, because it needs a lot of explanations to customers, and also need their cooperation to be performed Scalability and Replicability Deployment potential LV Centralised (SE & OPF) Voltage Control with OLTC & DG & LV Distributed (field measurements) Voltage Control with OLTC LV Distributed (field measurements) Voltage Control with OLTC, DG LV Distributed Voltage Control with AVR LV Distributed Voltage Control with DG LV Distributed Voltage Control with DG active power modulation LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with OLTC, DG LV Distributed Voltage Control with STATCOM LV Supervised (field measurements) Voltage Control with OLTC & DG LOW Table 31 Evaluated impact of scalability and replicability on deployment potential for LV voltage control solutions LOW V /12/18 36/126

116 The results on MV can be extrapolated to LV, being the most scalable solution the simplest one (Distributed control with OLTC). Centralised and supervised solutions are less scalable due to the same reasons exposed before, and DG Flexibility (active power modulation) is not easy to scale and replicate due to the need of modifying contracts and regulation requirements Reliability Deployment potential LV Centralised (SE & OPF) Voltage Control with OLTC & DG & LV Distributed (field measurements) Voltage Control with OLTC LV Distributed (field measurements) Voltage Control with OLTC, DG LV Distributed Voltage Control with AVR LV Distributed Voltage Control with DG LV Distributed Voltage Control with DG active power modulation LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with OLTC, DG LV Distributed Voltage Control with STATCOM LV Supervised (field measurements) Voltage Control with OLTC & DG Table 32 Evaluated impact of reliability on deployment potential for LV voltage control solutions The reliability of the LV monitoring solutions would be expected to be very similar to the MV voltage monitoring solution Risk on Investment Deployment potential LV Centralised (SE & OPF) Voltage Control with OLTC & DG & LV Distributed (field measurements) Voltage Control with OLTC LV Distributed (field measurements) Voltage Control with OLTC, DG LV Distributed Voltage Control with AVR LV Distributed Voltage Control with DG LV Distributed Voltage Control with DG active power modulation LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with OLTC, DG LV Distributed Voltage Control with STATCOM LOW V /12/18 37/126

117 LV Supervised (field measurements) Voltage Control with OLTC & DG Table 33 Evaluated impact of risk on investment on deployment potential for LV voltage control solutions The risk on investment of the LV voltage control solutions would be expected to be very similar to the MV voltage control solutions Technical Complexity Deployment potential LV Centralised (SE & OPF) Voltage Control with OLTC & DG & LV Distributed (field measurements) Voltage Control with OLTC LV Distributed (field measurements) Voltage Control with OLTC, DG LV Distributed Voltage Control with AVR LV Distributed Voltage Control with DG LV Distributed Voltage Control with DG active power modulation LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with OLTC, DG LV Distributed Voltage Control with STATCOM LV Supervised (field measurements) Voltage Control with OLTC & DG LOW Table 34 Evaluated impact of technical complexity on deployment potential for LV voltage control solutions A relatively high technical complexity would be expected for the solutions using centralised control systems. This would result in the expectation of a relatively low deployment potential Technical Requirements Deployment potential LV Centralised (SE & OPF) Voltage Control with OLTC & DG & LV Distributed (field measurements) Voltage Control with OLTC LV Distributed (field measurements) Voltage Control with OLTC, DG LV Distributed Voltage Control with AVR LV Distributed Voltage Control with DG LV Distributed Voltage Control with DG active power modulation LV Distributed Voltage Control with OLTC LOW V /12/18 38/126

118 LV Distributed Voltage Control with OLTC, DG LV Distributed Voltage Control with STATCOM LV Supervised (field measurements) Voltage Control with OLTC & DG LOW Table 35 Evaluated impact of technical requirements on deployment potential for LV voltage control solutions No centralised solutions are considered because of the size of the technical requirements needed to do it. Having centralized supervision on the secondary substations it s considered as MV Voltage Control/Monitoring Solution. This kind of solution could be feasible in a very restricted area. STATCOM solutions are discarded because they need more technical requirements than the others. Solutions using AVR are also discarded because they are not standard devices and more experience is needed by the DSO before these devices can be standardised. We consider than LV Voltage control using different combinations of elements or control devices like DG, OLTC are worth been studying further. We consider than the solution using field measurements in some critical nodes could improve the OLTC performance Regulatory and Market Requirements Deployment potential LV Centralised (SE & OPF) Voltage Control with OLTC & DG & LV Distributed (field measurements) Voltage Control with OLTC LV Distributed (field measurements) Voltage Control with OLTC, DG LV Distributed Voltage Control with AVR LV Distributed Voltage Control with DG LV Distributed Voltage Control with DG active power modulation LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with OLTC, DG LV Distributed Voltage Control with STATCOM LV Supervised (field measurements) Voltage Control with OLTC & DG LOW Table 36 Evaluated impact of regulatory requirements on deployment potential for LV voltage control solutions Additional regulatory requirement are needed in case of solutions using DG contribution. In some European countries today these contributions are not considered on the existing regulatory framework. V /12/18 39/126

119 3.4.9 Economical Requirements Deployment potential LV Centralised (SE & OPF) Voltage Control with OLTC & DG & LV Distributed (field measurements) Voltage Control with OLTC LV Distributed (field measurements) Voltage Control with OLTC, DG LV Distributed Voltage Control with AVR LV Distributed Voltage Control with DG LV Distributed Voltage Control with DG active power modulation LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with OLTC, DG LV Distributed Voltage Control with STATCOM LV Supervised (field measurements) Voltage Control with OLTC & DG LOW LOW Table 37 Evaluated impact of economical requirements on deployment potential for LV voltage control solutions In most cases, the MV/LV transformer in the secondary substation does not already have an OLTC installed. Most of the CAPEX becomes for this retrofitting. The other costs depend on the number of devices used, the communication infrastructure and the others retrofitting (PV inverters) needed to put in place the solutions. 3.5 MV Congestion Management Performance Deployment potential MV Congestion Management with DG non-firm grid connection contracts (including DG modulation) MV Congestion Management with Use of Flexibility (DG, DSM, Storage...) Table 38 Evaluated impact of performance on deployment potential for MV congestion management solutions The highest performing implementations are ones using all kind of flexibilities that DSO may contract: curtailment of generation, demand side management, storage, aggregators, etc. V /12/18 40/126

120 3.5.2 Social Aspects Deployment potential MV Congestion Management with DG non-firm grid connection contracts (including DG modulation) MV Congestion Management with Use of Flexibility (DG, DSM, Storage...) LOW Table 39 Evaluated impact of social aspects on deployment potential for MV congestion management solutions Regarding social aspects, the perception for the individual flexibilities to the congestion management of contribution to environment (include efficiency increase) could be positive (the customer will have the impression to participate on 2020 objectives). A special care will be made in case of installation of energy boxes or use of data from meters in order to maintain the consumers confidence about data privacy. Finally, the need of explanation of final customers to participate to this kind of mechanism could be an important issue Scalability and Replicability Deployment potential MV Congestion Management with DG non-firm grid connection contracts (including DG modulation) MV Congestion Management with Use of Flexibility (DG, DSM, Storage...) LOW LOW Table 40 Evaluated impact of scalability and replicability on deployment potential for MV congestion management solutions The most scalable solution is the simplest one. Solutions using all kind of flexibilities are less easy to scale up and replicate than the solutions using only non firm grid contracts. It is due to the fact that the need of communications is higher, as well as the need to involve a lot of participants. The results on MV can be extrapolated to LV Reliability Deployment potential MV Congestion Management with DG non-firm grid connection contracts (including DG modulation) MV Congestion Management with Use of Flexibility (DG, DSM, Storage...) Table 41 Evaluated impact of reliability on deployment potential for MV congestion management solutions The reliability of the MV congestion management solutions would be expected to be very similar to the MV voltage monitoring solution. V /12/18 41/126

121 3.5.5 Risk on Investment Deployment potential MV Congestion Management with DG non-firm grid connection contracts (including DG modulation) MV Congestion Management with Use of Flexibility (DG, DSM, STR...) LOW LOW Table 42 Evaluated impact of risk on investment on deployment potential for MV congestion management solutions Low scores were given to solutions to the following solutions to indicate a high risk on investment. This is based on existing regulation, standardisation and market frameworks. Congestion management solutions using storage There is still more work to do to establish market framework and regulation for the operation of storage facilities on distribution networks. A relatively high level of risk on investment would therefore be expected until this uncertainty is resolved. Controlling DG using non-firm grid connection contracts Under existing regulation, it is not possible for DSOs to control either active or reactive power of DG. Within the demonstration projects, control of the DG has been achieved using bilateral contracts on a voluntary basis. This of course would present a risk to any large scale deployment of these solutions unless regulatory change would allow the DSOs to control the DG Technical Complexity Deployment potential MV Congestion Management with DG non-firm grid connection contracts (including DG modulation) MV Congestion Management with Use of Flexibility (DG, DSM, Storage...) Table 43 Evaluated impact of technical complexity on deployment potential for MV congestion management solutions The technical complexity of the MV congestion management solutions would be expected to be very similar to the MV voltage control solutions Technical Requirements Deployment potential MV Congestion Management with DG non-firm grid connection contracts (including DG modulation) MV Congestion Management with Use of Flexibility (DG, DSM, Storage...) LOW Table 44 Evaluated impact of technical requirements on deployment potential for MV congestion management solutions We consider that the MV non-firm contracts, require fewer devices to be monitored and managed, than the use of flexibilities. Both need a SCADA integration in order to simulate and calculate the V /12/18 42/126

122 flexibility needed. Concerning the non-firm contracts, they need a bilateral communication between the DSO and the generator. For the use of flexibility, a communication between the DSO and one aggregator could be enough but it needs a market platform Regulatory and Market Requirements Deployment potential MV Congestion Management with DG non-firm grid connection contracts (including DG modulation) MV Congestion Management with Use of Flexibility (DG, DSM, Storage...) LOW LOW Table 45 Evaluated impact of regulatory requirements on deployment potential for MV congestion management solutions Additional regulatory requirements are needed for both solutions in the majority of the European countries. DG connections contracts are often defined with a fit and forget approach and the active power curtailment are not allowed. In addition, the use of flexibility needs to define an appropriate market framework and an appropriate regulation framework in order to design how the DSO will be cover its costs generated by the economic compensation to be paid to the aggregators for the services provided Economical Requirements Deployment potential MV Congestion Management with DG non-firm grid connection contracts (including DG modulation) MV Congestion Management with Use of Flexibility (DG, DSM, Storage...) LOW Table 46 Evaluated impact of economical requirements on deployment potential for MV congestion management solutions The costs depend on the number of devices used. For the non-firm connection contracts we consider than only new generators contracts have access and not retrofitting is needed. We need only to adapt existing planning tools in order to calculate the possible network constraints during the connection contract duration and of the operational tools (SE+OPF). The use of flexibility will be open to all the flexibilities even those already connected to the network so some retrofitting could be necessary. This solution also needs tool adaptations: Planning tools/operational tools (in order to detect the network constraints), SCADA (in order to sent the set point to the DG), market platform (in order to receipt and activate the flexibility offers and to ensure the settlement process). In addition the aggregator needs to communicate with the individual flexibilities and also with the DSO through the market platform. Energy boxes or other similar devices installed at each individual flexibility level. V /12/18 43/126

123 3.6 LV Congestion Management Performance Deployment potential LV Congestion Management with DG non-firm grid connection contracts (including DG modulation) LV Congestion Management with Use of Flexibility (DG modulation, DSM, Storage...) Table 47 Evaluated impact of performance on deployment potential for LV congestion management solutions The highest performing implementations are ones using all kind of flexibilities that DSO may contract: curtailment of generation, demand side management, storage, aggregators, Social Aspects Deployment potential LV Congestion Management with DG non-firm grid connection contracts (including DG modulation) LV Congestion Management with Use of Flexibility (DG modulation, DSM, STR...) LOW Table 48 Evaluated impact of social aspects on deployment potential for LV congestion management solutions Regarding social aspects, the perception for the individual flexibilities to the congestion management of contribution to environment (include efficiency increase) could be positive (the customer will have the impression to participate on 2020 objectives). A special care will be made in case of installation of energy boxes or use of data from meters in order to maintain the consumers confidence about data privacy. Finally, the need of explanation of final customers to participate to this kind of mechanism could be an important issue Scalability and Replicability Deployment potential LV Congestion Management with DG non-firm grid connection contracts (including DG modulation) LV Congestion Management with Use of Flexibility (DG modulation, DSM, Storage...) LOW LOW Table 49 Evaluated impact of scalability and replicability on deployment potential for LV congestion management solutions The results on MV can be extrapolated to LV, being the most scalable solution the simplest one. Solutions using all kind of flexibilities are less easy to scale up and replicate than the solutions V /12/18 44/126

124 using only non firm grid contracts. It is due to the fact that the need of communications is higher, as well as the need to involve a lot of participants Reliability Deployment potential LV Congestion Management with DG non-firm grid connection contracts (including DG modulation) LV Congestion Management with Use of Flexibility (DG modulation, DSM, STR...) Table 50 Evaluated impact of reliability on deployment potential for LV congestion management solutions A high level of reliability would be expected from both implementations Risk on Investment Deployment potential LV Congestion Management with DG non-firm grid connection contracts (including DG modulation) LV Congestion Management with Use of Flexibility (DG modulation, DSM, Storage...) LOW LOW Table 51 Evaluated impact of risk on investment on deployment potential for LV congestion management solutions The reliability of the LV congestion management solutions would be expected to be very similar to the MV voltage monitoring solution Technical Complexity Deployment potential LV Congestion Management with DG non-firm grid connection contracts (including DG modulation) LV Congestion Management with Use of Flexibility (DG modulation, DSM, Storage...) LOW LOW Table 52 Evaluated impact of technical complexity on deployment potential for LV congestion management solutions The technical complexity of the LV congestion management solutions would be expected to be very similar to the LV voltage monitoring solutions. V /12/18 45/126

125 3.6.7 Technical Requirements Deployment potential LV Congestion Management with DG non-firm grid connection contracts (including DG modulation) LV Congestion Management with Use of Flexibility (DG modulation, DSM, Storage...) LOW LOW Table 53 Evaluated impact of technical requirements on deployment potential for LV congestion management solutions The criteria are very similar to those of MV congestion management. For LV, the problem is the high number of device to be managed (large number of individual generators and the individual consumers should be simulated in order to check if its flexibility solve the network constraints) Regulatory and Market Requirements Deployment potential LV Congestion Management with DG non-firm grid connection contracts (including DG modulation) LV Congestion Management with Use of Flexibility (DG modulation, DSM, Storage...) LOW LOW Table 54 Evaluated impact of regulatory requirements on deployment potential for LV congestion management solutions Additional regulatory requirements are needed for both solutions in the majority of the European countries. DG connections contracts are often defined with a fit and forget approach and the active power curtailment are not allowed. In addition, the use of flexibility needs to design an appropriate market framework and an appropriate regulation framework in order to define how the DSO will be cover its costs generated by the economic compensation to be paid to the aggregators for the services provided Economical Requirements Deployment potential LV Congestion Management with DG non-firm grid connection contracts (including DG modulation) LV Congestion Management with Use of Flexibility (DG modulation, DSM, Storage...) LOW LOW Table 55 Evaluated impact of economical requirements on deployment potential for LV congestion management solutions The criteria are very similar that those of MV Congestion Management. But in this case the number of individual flexibilities is multiplied by thousands. Potentially each individual generator and residential consumer could be interested to participate in this kind of mechanisms. V /12/18 46/126

126 4 Annex C: SRA Solutions description This chapter includes a description of the most promising solutions (implementations) selected for the scalability and replicability analysis. These are grouped into the following four functionalities being each explained in a different sub-section of this chapter: MV Voltage Monitoring LV Voltage Monitoring MV Voltage Control LV Voltage Control MV Congestion Management 4.1 MV Voltage Monitoring implementations The following MV Voltage Monitoring solutions/implementations are considered for the analysis: 1. MV Voltage Monitoring (RTU) 2. MV Voltage Monitoring (SE) 3. MV Voltage Monitoring (PLF) It is clear that MV monitoring enables better operation of the network, improved service and helps to identify the remaining capacity of the network to handle further demand or generation increases. The first result of the comparison is aimed to explore the preferences/willingness for two types of solutions. The first one is based on a few measurements from some limited number of critical nodes and relies on the correct network planning and on the experience to the network operators to cope with the remaining uncertainty. The second one could need a larger number of measurements to feed a distribution state estimation and achieves a snapshot of the real conditions of the network but also enables other functionalities. Another result focuses on two main alternatives: deterministic (RTU, SE) and stochastic tools (PLF). It is obvious that deterministic mechanisms are in place today but it is wanted to find out the chances for the stochastic ones in the future. In any case it seems better having an approximate state than nothing at all if the cost justifies it. V /12/18 47/126

127 MV Voltage Monitoring (RTU) Functionality MV network monitoring Short description It is based on transmitting real-time remote measurement from a few critical nodes to the SCADA system located in the distribution control centre. It is a deterministic tool. Problems addressed Uncertainty of the distribution network state Expected benefits Monitoring of voltage at some MV critical points provided to the distribution network operator (Implicit assessment of the remaining hosting capacity / implicit distribution network investment deferrals ) Control type N/A (Control Centre) Control system tools SCADA Measurement nodes Remote from the MV critical nodes to the control centre Controlled devices None Solution requirements SCADA Unidirectional communications on pseudo real-time 1. Risks In case of switching operations the network topology could vary so the selection of the critical nodes may not fully reflect the new critical nodes so facing the risk of voltage limit violation. Comments It is assumed that measurements from a few critical nodes may help an experienced network operator into identifying the real estate of the network. The MV Voltage Monitoring (SE) solution may require a higher number of measurements. This solution is aimed to networks in which the hosting capacity is clearly limited by the voltage (and not by the current). Table 56 MV Voltage Monitoring (field measurement) description 1 The additional measurements from the critical nodes. V /12/18 48/126

128 MV Voltage Monitoring (SE) Functionality MV network monitoring Short description A State Estimation (SE) algorithm calculates the most probable status of the system based on the gathered data from SCADA. The SE requires a larger set of measurements and pseudo-measurements but improves MV network observability. It is a deterministic tool. Problems addressed Uncertainty of the distribution network state Expected benefits Warning in real time of voltage and/or thermal constraints al MV provided to the distribution network operator. (Implicit assessment of the remaining hosting capacity / implicit distribution network investment deferrals ) Control type N/A (Control Centre) Control system tools SCADA Measurement nodes Remote from MV nodes (critical, DGs ) to the control centre Remote from (some) MV DGs to the control centre Controlled devices None Solution requirements SCADA Unidirectional communications on pseudo real-time Risks None Comments This solution should be compared to MV Voltage Monitoring (field measurements) not only in terms of cost and performance. The SE solution could serve to feed advanced applications and relies less on operator experience. This solution has a priori a higher (technical) replication potential. Table 57 MV Voltage Monitoring (SE) description V /12/18 49/126

129 MV Voltage Monitoring (PLF) Functionality MV network monitoring Short description It is an off-line calculation. A Probabilistic Load Flow (PLF) algorithm carries out probabilistic predictions of voltage profiles at network buses and feeder power flows based on forecasted demand and generation. Problems addressed Uncertainty of the distribution network state Expected benefits Warning in advance of potential voltage and/or thermal constraints al MV provided to the distribution network operator. (Implicit assessment of the remaining hosting capacity / implicit distribution network investment deferrals ) Control type N/A (Control Centre) Control system tools Energy generation forecasting tool Energy demand forecasting tool Probabilistic Load Flow Measurement nodes Off-line daily download of load and generation MV measurements by the remote metering infrastructure Controlled devices None Solution requirements Metering infrastructure Weather forecast Risks None Comments Table 58 MV Voltage Monitoring (PLF) description 4.2 LV Voltage Monitoring implementations There is only one solution/implementation for the LV Monitoring functionality: 1. LV Voltage Monitoring (AMI) This implementation is considered for the SRA. The need for LV monitoring along the time is evaluated. Even more the use of the smart meters is suggested as possible mechanisms knowing in advance that in the deployment of smart meters is subject to a cost benefit analysis which turned V /12/18 50/126

130 to be negative in some countries (e.g. Germany) or that most of the already deployed smart meters cannot measure and process the voltage. In any case some countries may experience problems at low density residential areas where incentives for domestic PV could increase the penetration levels leading to challenges on the operation of the LV network in the future. LV Voltage Monitoring (AMI) Functionality LV network monitoring Short description It is an off-line calculation. A process/ algorithm analyses the values of voltage measurements recorded by the smart meters. Problems addressed Uncertainty of the distribution network state Expected benefits Identification of voltage constraints appearing at LV network. Assessment of the remaining hosting capacity Control type N/A (Control Centre) Control system tools Custom analysis application processing off-line meter data Smart Meters recording the voltage per phase Measurement nodes Off-line periodic download of LV voltage values by the remote metering infrastructure Controlled devices None Solution requirements Metering infrastructure Meters able to perform, record and transmit voltage measurements Risks Later regulatory changes may limit the access to individual customer meter data Bugs or discovered cyber security issues may require to disable the functionality / upgrade devices / replace them Comments Austrian pilot project (the use case is not included in IGREENGrid) The already deployed AMI may not support the required functionality (LV voltage measurements): meters, data concentrators, comm. Protocols, etc. which would severely limit the replication potential for some DSOs / countries. In case of topology change the smart meter data must be flagged to avoid drawing wrong analyses. Table 59 LV Supervised Voltage Control (AMI) description V /12/18 51/126

131 4.3 MV Voltage Control implementations There are several implementations of the MV Voltage Control functionality: 1. MV Distributed Voltage Control with OLTC 2. MV Distributed Voltage Control with OLTC, DG 3. MV Centralised (field measurements) Voltage Control with OLTC 4. MV Supervised (field measurements) Voltage Control with OLTC & DG 5. MV Supervised Voltage Control with OLTC & DG 6. MV Centralized (SE) Voltage Control with OLTC 7. MV Centralised (SE & OPF) Voltage Control with OLTC & DG The different solutions for the MV Voltage control problem offer some differences among them in terms of implementation, communication means, complexity of the algorithms and tools etc. so the added value of some of the approaches can be evaluated. The MV Distributed Voltage Control with OLTC represents the Business as Usual 2. It is then compared to two possible alternatives: fist adding the local control of MV DGs adapting the reactive power injection/consumption as a function of the local measured voltage ( MV Distributed Voltage Control with OLTC, DG ) and second improving the HV/MV transformer OLTC control as to consider remote measurements from MV critical nodes for tap setting ( MV Centralised (field measurements) Voltage Control with OLTC ). The improved HV/MV transformer OLTC control is enhanced one step ahead by enabling the control of the reactive power provision by MV DGs in a coordinated manner applying slightly different algorithms and compared among them ( MV Supervised (field measurements) Voltage Control with OLTC & DG and MV Supervised Voltage Control with OLTC & DG ). MV Centralized (SE) Voltage Control with OLTC solution uses advanced DMS tools to calculate a better and more complete estimation of the network state than that obtained with for a few critical nodes for OLTC control. The last implementation ( MV Centralised (SE & OPF) Voltage Control with OLTC & DG ) deploys another advanced DMS tool traditionally found at transmission network control centres: the optimal power flow. 2 This is equivalent to do nothing scenario in terms of smart solution deployment. V /12/18 52/126

132 MV Distributed Voltage Control with OLTC Functionality MV Voltage Control Short description The local control of the primary substation adjusts the turn ratio of the HV/MV transformer based on local measurements to maintain desired voltage level at the MV network. Problems addressed Quality of Supply at MV networks. Expected benefits Hosting capacity for DRES in LV distribution grids Voltage quality performance Control type Distributed (HV/MV Substation) Control system tools HV/MV Transformer OLTC control Measurement nodes Local at HV/MV substation Controlled devices HV/MV Transformer OLTC Solution requirements None Risks None Comments This solution represents the classical approach (Business as Usual / Do Nothing scenario for WP5 purposes). The OLTC of the HV/MV transformer has been the traditional unattended mechanism for MV voltage control compensating HV voltage and demand variations; Capacitor banks may also form part of the solution. Table 60 MV Distributed Voltage Control with OLTC description V /12/18 53/126

133 MV Distributed Voltage Control with OLTC, DG Functionality MV Voltage Control Short description This solution is based on the conventional management of the OLTC of the HV/MV transformer adding a local control mechanism at MV DGs so reactive power injection is adjusted depending on the local voltage. Problems addressed Quality of Supply at MV networks. Expected benefits Hosting capacity for DRES in MV distribution grids Voltage quality performance Control type Distributed (HV/MV Substations) Distributed (MV DG) Control system tools HV/MV Transformer OLTC control MV DG local control logic Measurement nodes Local at HV/MV substation (no communication needed) Local at MV DG (no communication needed) Controlled devices HV/MV Transformer OLTC MV DG reactive power 3 [MV DG reactive power & MV DG active power. 4 ] Solution requirements None Risks Regulatory changes defining MV DG local control functionality as a service or as a compulsory connection condition. Comments French pilot project (UC.FR.01) This solution should be compared to MV Distributed Voltage Control with OLTC ; the additional control is based on the local measurements by the MV DG control units adapting reactive power injection accordingly to the local voltage. Table 61 MV Distributed Voltage Control with OLTC, DG description 3 There is some automatic local control in place adjusting the reactive power to the measured voltage. If so, the service provision could be requested by the regulation and the MV grid codes. 4 The DG active power limitation could be built into the local control as security mechanism in contrast to curtailment that could be associated to a DSO issued order. V /12/18 54/126

134 MV Centralised (field measurements) Voltage Control with OLTC Functionality MV Voltage Control Short description This approach improves the control of the transformer OLTC at the HV/MV substation by adding remote measurements from some critical nodes of the MV network. The control is triggered when some of the sensed voltages are out of the statutory limits bringing the MV voltage levels back within the threshold. Problems addressed Quality of Supply at MV networks. Expected benefits Hosting capacity for DRES in MV distribution grids Voltage quality performance Control type Centralised Control system tools HV/MV Transformer OLTC control The OLTC differs from the standard control into considering MV measurements as triggering mechanism for actuation. Measurement nodes Remote at HV/MV substation (communication needed) Remote from some MV critical nodes (communication needed) Controlled devices HV/MV Transformer OLTC Solution requirements Voltage measurements from the MV critical nodes Unidirectional on-demand communications without special speed, latency, capacity requirements. A GPRS based communication network may be enough Risks If in use, the third party communications infrastructure may become obsolete sooner than expected (i.e. 3G communications being replaced by 4G) Comments German pilot project (UC.DE.03 Wide Area Control) This solution represents a step forward from MV Distributed Voltage Control with OLTC adding information from MV Voltage sensors into the OLTC control logic. In many cases, the penetration of DRES into the MV feeders supplied from the same HV/MV substation is not uniform so the traditional OLTC logic based on local measurements may be improved by considering real time measurements from a few MV nodes. The identification of the MV critical nodes is almost straight forward from MV planning network studies. Topology changes (outage, maintenance. service restoration.) may change the list of MV critical nodes. The OLTC control logic is triggered when voltage field measurements indicate a voltage violation. The loss of the communication channel along the standard operation is common for a few minutes; This is compensated because there are several critical nodes and not every time the communication is broken the solution should be called in. Table 62 MV Centralised (field measurements) Voltage Control with OLTC description V /12/18 55/126

135 MV Supervised (field measurements) Voltage Control with OLTC & DG Functionality MV Voltage Control Short description The solution is based on a distributed control placed at the HV/MV substation. The control algorithm manages the HV/MV transformer OLTC based on field measurements from the MV to ensure that MV voltage level is adequate and is also able to issue reactive power commands to MV DGs when needed. Problems addressed Quality of Supply at MV networks. Expected benefits Hosting capacity for DRES in MV distribution grids Voltage quality performance Control type Supervised (HV/MV Substations) Control system tools HV/MV Transformer OLTC control The OLTC differs from the standard control into considering MV measurements as triggering mechanism for actuation. Additionally, the reactive power injection of the distributed generators connected to the MV network can also be commanded. The algorithm manages the MV overall voltage range by acting over the HV/MV OLTC tap and adjusts the reactive power provision of some MV DG units if needed. The control acts in a supervised manner as it only issues orders when needed. Measurement nodes Local at HV/MV substation Remote from some MV critical nodes to the HV/MV substation (communication needed) Remote from some MV DGs to the HV/MV substation (communication needed) Controlled devices HV/MV Transformer OLTC MV DG reactive power [MV DG active power] 5 Solution requirements Voltage measurements from the MV critical nodes MV DG units enabled to follow external reactive power commands Bidirectional communications without special speed, latency, capacity requirements. A GPRS based communication network may be enough The regulation should enable the provision of reactive power support by MV DG units following the commands of the DSO 6 Risks If in use, the third party communications infrastructure may become obsolete sooner than expected (i.e. 3G communications being replaced by 4G) The performance of the solution may be linked to the presence of a few DG units following their 5 If needed DG active power could be also managed. The term management is intentionally unspecific into including from DSO-DG Operator flexibility contracts to curtailment. 6 Again, the specific arrangements (regulated, private contract, open market ) for this service provision are left out. V /12/18 56/126

136 own business objectives. A regulatory change may affect to the reactive power provision service (i.e. change on tariffs, modification of incentives ) leading to changes on the performance of the solution. Comments Austrian pilot project (UC.AT.03) This solution changes from MV Supervised (field measurements) Voltage Control with OLTC adding the reactive power injection of some MV DG units. The incremental change on the solution performance should justify the higher costs. The remaining ideas from the previous solution (how topology changes affect, impact of communication loss. etc.) also apply here. Table 63 MV Supervised (field measurements) Voltage Control with OLTC & DG description V /12/18 57/126

137 MV Supervised Voltage Control with OLTC & DG Functionality MV Voltage Control Short description This solution is based on a central SCADA system receiving field measurements and alarms. Under normal operation. MV DGs adapt their reactive power injection to the local conditions of the grid and send an alarm when reaching their limit. A centralized algorithm adjusts the HV/MV transformer OLTC and the reactive power provision from the remaining MV DGs as to satisfy the expected quality of supply target. Problems addressed Quality of Supply at MV networks. Expected benefits Hosting capacity for DRES in MV distribution grids Voltage quality performance Control type Supervised (Control Center) Control system tools SCADA Topology processor tracking switch gear changes. Centralized control calculation for HV/MV Transformer OLTC tap. The centralized voltage control is activated when a MV DG unit signals that its limit for reactive power has been reached and the voltage is out of the limits. The control combines the management of the HV/MV OLTC tap setting with a sensibility matrix used to identify which reactive power control will achieve higher impact on the target voltage. Again the control operates in supervised mode as it only issues orders to return to a secure and satisfactory network state. Measurement nodes Remote from HV/MV substations to the control centre Remote from the managed MV DGs to the control centre Controlled devices HV/MV Transformer OLTC MV DG reactive power Solution requirements MV DG units enabled to follow external reactive power commands SCADA Bidirectional communications on pseudo real-time. The regulation should enable the provision of reactive power support by MV DG units following the commands of the DSO 7 Risks If in use, the third party communications infrastructure may become obsolete sooner than expected (i.e. 3G communications being replaced by 4G) The performance of the solution may be linked to the presence of a few DG units following their own business objectives. A regulatory change may affect to the reactive power provision service (i.e. change on tariffs, 7 Again, the specific arrangements (regulated, private contract, open market ) for this service provision are left out. V /12/18 58/126

138 modification of incentives ) leading to changes on the performance of the solution. Comments Italian pilot project (UC.IT.01) This solution differs from MV Supervised Voltage Control with OLTC & DG on where the main control is located, the inclusion of the topology processor and on the details of the algorithm. In this particular case, the approach taken by ENEL 8 to centralize distribution network control, deploy a relatively high number of MV nodes with measurements/automation/remote access; consider topology changes as normal business pushes high the relevance of this solution. Table 64 MV Supervised Voltage Control with OLTC & DG description 8 The DMS software is upgraded periodically to include new functions and then installed to every control centre; Functions that are not in use are disabled for each control dispatch but automatically available for all of them in case field devices support these advanced tools. V /12/18 59/126

139 MV Centralized (SE) Voltage Control with OLTC Functionality MV Voltage Control Short description The MV Centralized (SE) Voltage Control with OLTC solution employs a Distribution State Estimator to build a reliable snapshot of the MV network situation and issues control orders to modify the turn ratio of the HV/MV transformer through the OLTC tap if needed. The DSE runs over the measurements acquired by the central SCADA system. Problems addressed Quality of Supply at MV networks. Expected benefits Hosting capacity for DRES in MV distribution grids Voltage quality performance Control type Centralized Control system tools SCADA Distribution State Estimation HV/MV Transformer OLTC tap based on the DSE solution identifying potential voltage violations. The control operates on continuous mode and minimizes the number of changes of the HV/MV transformer OLTC tap position. Measurement nodes Remote from HV/MV substations to the control centre Remote from some MV nodes and/or MV DG units to the control centre 9 Controlled devices HV/MV Transformer OLTC Solution requirements SCADA DSE 10 Bidirectional communications on pseudo real-time. Risks If in use, the third party communications infrastructure may become obsolete sooner than expected (i.e. 3G communications being replaced by 4G) Comments French pilot project (UC.FR.02) When compared to MV Distributed (field measurements) Voltage Control with OLTC this solution uses centralized approach based on a distribution state estimation assumed to require a higher number of measurements that those for a few critical nodes. The comparison with MV Supervised Voltage Control with OLTC & DG is not so easy. Both require SCADA and remote field communications but the management of DG reactive power may introduce better performance on the voltage control objective but also higher complexity. It is important to note that the DSE may identify not only voltage constraints but also those linked to branches thermal limits. Table 65 MV Centralized (SE) Voltage Control with OLTC description 9 Any additional measuring device required for the validation of the DSE at the demo site is not considered here. 10 The DSE may require pseudo-measurements from load profiles, generation profiles, etc. These are not listed here. V /12/18 60/126

140 MV Centralised (SE & OPF) Voltage Control with OLTC & DG Functionality MV Voltage Control Short description This is the most complex solution in terms of tools. The Distribution Management System includes a distribution state estimator to calculate a network image used latter on to feed an Optimal Power Flow in charge of solving any network constraint and defining the set of actions as to achieve some objective function (i.e. losses reduction, minimization of reactive power.). The set of conventional network elements used to manage MV voltage levels (HV/MV transformer OLTC, capacitor banks.) is widened as to include the reactive power support from MV DG. Problems addressed Quality of Supply at MV networks. Expected benefits Hosting capacity for DRES in MV distribution grids Voltage quality performance Control type Centralized Control system tools SCADA Distribution State Estimation Optimal Power Flow. The OPF is usually designed to first solve network constraints if any and then to support several alternative objective functions (i.e. minimization of network losses, minimization of reactive power injection ) The control operates on continuous mode. Measurement nodes Remote from HV/MV substations to the control centre Remote from some MV nodes and/or MV DG units to the control centre 11 (communication needed) Controlled devices HV/MV Transformer OLTC MV DG reactive power 12 [MV DG active power] 13,14 Solution requirements SCADA DSE 15 OPF MV DG units enabled to follow external reactive power commands Bidirectional communications on pseudo real-time. 11 Any additional measuring device required for the validation of the DES at the demo site is not considered here. 12 Some devices such as a MV STATCOM may be considered as a special case of custom device installed to fulfil DSO needs for reactive power provision. 13 If needed DG active power could be also managed. The term management is intentionally unspecific into including from DSO-DG Operator flexibility contracts to curtailment. 14 Some devices such as a MV Storage may be considered as a special case of custom device installed to fulfil DSO needs for active power provision. 15 The DSE may require pseudo-measurements from load profiles, generation profiles, etc. These are not listed here. V /12/18 61/126

141 The regulation should enable the provision of reactive power support by MV DG units following the commands of the DSO 16 Risks If in use, the third party communications infrastructure may become obsolete sooner than expected (i.e. 3G communications being replaced by 4G) The performance of the solution may be linked to the presence of a few DG units following their own business objectives. A regulatory change may affect to the reactive power provision service (i.e. change on tariffs, modification of incentives ) leading to changes on the performance of the solution. Comments Austrian pilot project (UC.AT.01) and Spanish pilot project (UC.ES.02) If compared with MV Distributed (field measurements) Voltage Control with OLTC & DG this solution applies a centralized approach based on a distribution state estimation and calculates the optimal solution. The introduction of the OPF and the control over MV DG reactive power summarizes the distinction to MV Centralized (SE) Voltage Control with OLTC ; The increased performance should support the increased costs. In theory, it would require a higher number of measurements but also lead to better monitoring of the MV network state (voltage and power flows). The OPF should perform better than a simplified sub-optimal as well as support several optimization targets. At UC.AT.01 the reactive power support from some MV DGs is exploited while at UC.ES.02 the reactive power injection comes from a STATCOM. Table 66 MV Centralised (SE & OPF) Voltage Control with OLTC & DG description 16 The specific arrangements (open market, private contract, regulated ) for this service provision are left out. V /12/18 62/126

142 4.4 LV Voltage Control implementations There are several solutions/implementations for the LV Voltage control functionality: 1. LV Distributed Voltage Control with OLTC 2. LV Distributed Voltage Control with DG 3. LV Distributed Voltage Control with OLTC, DG 4. LV Distributed (field measurements) Voltage Control with OLTC, DG The main assumption for selecting the solutions is that due to the large number of MV/LV substations, the number of devices and the extension of the LV network it wouldn t be reasonable to outline centralized solutions so distributed ones would be preferred. For instance, if the MV/LV transformer has an OLTC the tap would be calculated by the local control logic, and there would not be a central application in charge of it. There are tens, even hundreds of thousands of MV/LV substations and millions of customer premises. The set of solutions is formed with different combinations of MV/LV transformer OLTC and LV DG local control (likely to be inverter based) operating separately ( LV Distributed Voltage Control with OLTC & LV Distributed Voltage Control with DG ) or in parallel but independently ( LV Distributed Voltage Control with OLTC, DG & LV Distributed (field measurements) Voltage Control with OLTC, DG ). These solutions are aimed to be compared among them in terms of performance introducing progressively communications and complexity. So the final purpose is to evaluate if increased costs are paid with better results. The study of LV DG local control only based solutions should help into supporting the recommendation request of LV Grid Codes for reactive power control as function of the local voltage and LV Grid Codes for active power control self-limitation (avoiding the word curtailment). It was mentioned several times along the meeting in Paris and many countries lack of regulation for this sort of controls. V /12/18 63/126

143 LV Distributed Voltage Control with OLTC Functionality LV Voltage Control Short description This alternative applies a local controller located at the MV/LV substation managing the MV/LV transformer OLTC from local measurements. The presence of LV DG along the LV feeders could lead to voltage issues mismanaged by the local controller. Problems addressed Quality of Supply at LV networks. Expected benefits Voltage quality performance Control type Distributed (MV/LV Subs.) Control system tools MV/LV transformer OLTC control logic Measurement nodes Local at MV/LV substation (no communication needed) Controlled devices MV/LV transformer OLTC Solution requirements MV/LV transformer with OLTC 17 No communications. Risks Comments The Austrian pilot project combines the MV/LV transformer OLTC with local DG controls. The demonstrator focuses on low density residential area with a relatively high penetration of LV PV based generation studying and comparing different alternatives for guaranteeing LV quality of supply. This solution is introduced as a simplified version of more complex alternatives for comparison purposes of the relative gain in performance. In a more general situation, the MV/LV transformer OLTC may serve to solve voltage quality issues at some specific LV locations isolating LV network voltage from MV network voltage. Table 67 LV Distributed Voltage Control with OLTC description 17 The MV/LV transformer with OLTC is listed here as solution requirement as these devices are not common. The great majority of MV/LV transformers have an off-load off-voltage tap changer. V /12/18 64/126

144 LV Distributed Voltage Control with DG Functionality LV Voltage Control Short description This solution applies the local LV DG controller to modify Q (and P&Q) considering the local voltage measured at the DG connection point. Problems addressed Quality of Supply at LV networks. Expected benefits Hosting capacity for DRES in LV distribution grids Voltage quality performance Control type Distributed (LV DG) Control system tools LV DG local control logic (Both controls operate independently one from another) Measurement nodes Local at LV DG connection point (no communication needed) Controlled devices LV DG reactive power 18 [LV DG reactive power & LV DG active power 19,20 ] Solution requirements LV DG with local control for reactive/active power control. No communications. The regulation should enable the provision of reactive power support by LV DG units following a suitable LV Grid Code 21 Risks Regulatory changes defining LV DG local control functionality as a service or as a compulsory connection condition. Comments The Austrian pilot project combines the MV/LV transformer OLTC with local DG controls. This solution is introduced as a simplified version of more complex alternatives for comparison purposes of the relative gain in performance. In theory it could be a cost free solution for the DSO as the LV DG local control is deployed and paid by the DG owner and the requested functionality would be specified as LV grid code. Table 68 LV Distributed Voltage Control with DG description 18 Due the expected high number of devices it would be preferable some automatic local control in place adjusting the reactive power to the measured voltage. If so, the service provision would be imposed by the regulation and the LV grid codes. 19 In the case of LV networks the DG active power limitation seems more effective than reactive power control. 20 The DG active power limitation is built into the local control as security mechanism in contrast to curtailment that could be associated to a DSO issued order. 21 If the grid code specifies these sort of control then there is not a service provision but a grid access technical requirement. V /12/18 65/126

145 LV Distributed Voltage Control with OLTC, DG Functionality LV Voltage Control Short description It is a distributed control that comprises first a local controller located at the MV/LV substation managing the MV/LV transformer OLTC from only local measurements. In parallel, the local LV DG controller modulates Q (and P&Q) depending on the local voltage. Problems addressed Quality of Supply at LV networks. Expected benefits Hosting capacity for DRES in LV distribution grids Voltage quality performance Control type Distributed (MV/LV Substations) Distributed (LV DG) Control system tools MV/LV transformer OLTC control logic LV DG local control logic (Both controls operate independently one from another) Measurement nodes Local at MV/LV substation (no communication needed) Local at LV DG connection point (no communication needed) Controlled devices MV/LV transformer OLTC LV DG reactive power 22 [LV DG reactive power & LV DG active power 23,24 ] Solution requirements MV/LV transformer with OLTC 25 LV DG with local control for reactive/active power control. No communications. The regulation should enable the provision of reactive power support by LV DG units following a suitable LV Grid Code 26 Risks Regulatory changes defining LV DG local control functionality as a service or as a compulsory connection condition. Comments Austrian pilot project (UC.AT.04) This solution merges the two types of LV local control aimed for voltage control under the same case study. Both controls are operating at the same time but independently one from the other. Table 69 LV Distributed Voltage Control with OLTC, DG description 22 Due the expected high number of devices it would be preferable some automatic local control in place adjusting the reactive power to the measured voltage. If so, the service provision would be imposed by the regulation and the LV grid codes. 23 In the case of LV networks the DG active power limitation seems more effective than reactive power control. 24 The DG active power limitation is built into the local control as security mechanism in contrast to curtailment that could be associated to a DSO issued order. 25 The MV/LV transformer with OLTC is listed here as solution requirement as these devices are not common. The great majority of MV/LV transformers have an off-load off-voltage tap changer. 26 If the grid code specifies these sort of control then there is not a service provision but a grid access technical requirement. V /12/18 66/126

146 LV Distributed (field measurements) Voltage Control with OLTC, DG Functionality LV Voltage Control Short description It is a distributed control that comprises first a local controller located at the MV/LV substation managing the MV/LV transformer OLTC from both local measurements and some LV network measurements. In parallel, the local LV DG controller modulates Q (and P&Q) depending on the local voltage. Problems addressed Quality of Supply at LV networks. Expected benefits Hosting capacity for DRES in LV distribution grids Voltage quality performance Control type Distributed (MV/LV Substations) [Distributed (LV DG)] Control system tools MV/LV transformer OLTC control logic. The OLTC control algorithm integrates LV field measurements into the logic to calculate the tap setting. LV DG local control logic (Both controls operate independently one from another) Measurement nodes Local at MV/LV Substation Remote at some LV critical nodes to the MV/LV Substation Local at LV DG connection point Controlled devices MV/LV transformer OLTC LV DG reactive power [LV DG reactive power & LV DG active power] Solution requirements MV/LV transformer with OLTC LV DG with local control for reactive/active power control. Unidirectional on-demand communications without special speed, latency, capacity requirements. The regulation should enable the provision of reactive power support by LV DG units following a suitable LV Grid Code Risks Regulatory changes defining LV DG local control functionality as a service or as a compulsory connection condition. Comments Austrian pilot project (UC.AT.05) This solution should be compared to LV Distributed Voltage Control with OLTC, DG ; The additional element of based on the inclusion of some field measurements from the LV network into the algorithm controlling the MV/LV transformer OLTC. The increased performance should be compared to the higher complexity and costs. V /12/18 67/126

147 In the particular case of the Austrian pilot project, the LV voltage measurements are obtained from the advanced metering infrastructure. A few smart meters can respond fast enough as to obtain pseudo-real time measurements and these measurements characterize the LV network state. Even more these smart meters are able to provide voltage measurements and this functionality may not be supported by many other meters allowing remote metering. Table 70 LV Distributed (field measurements) Voltage Control with OLTC, DG description V /12/18 68/126

148 4.1 MV Congestion Management implementations The following MV Congestion Management implementations are considered for the analysis: 1. MV Congestion Management with DG non-firm grid connection contracts (including DG modulation) 2. MV Congestion Management with Use of Flexibility (DG, DSM, storage...) MV Congestion Management with DG non-firm grid connection contracts (including DG modulation) Functionality MV Congestion Management Short description The DSO sends set points for modulation to each individual DG generator connected to the MV as planned on its DG connection contracts. Problems addressed Facilitate the connection procedures. Management of congestion of MV network (voltage, current ) Expected benefits Reduce the connection cost for the DG and the delay for connection Control type Centralised Control system tools Planning tools (to establish the connection contract), operational tools (in order to detect the network constraints), SCADA (in order to send the set point to the DG) Measurement nodes DG connection node Controlled devices DG devices to communicate with the DSO paid by the generator Solution requirements SE&OPF Risks Undervalue the value of energy to be modulate or the number of hours Comments It is needed to adapt the existing connection studies (in order to determine the conditions of the DG modulation (i.e. number of hours by year, energy volume to be modulated ). This studies already done it at MV level for the connection of DG need some kind of planning tools in order to calculate the possible network constraints during the connection contract duration Table 71 MV Congestion Management with DG non-firm grid connection contracts description V /12/18 69/126

149 MV Congestion Management with Use of Flexibility (DG, DSM, storage...) Functionality MV Congestion Management Short description All kind of flexibilities that a DSO may contract through a market platform : Modulation of generation, Demand side management, Storage, Aggregators... Flexibilities could be contract in a long term or in short-term depending when the networks constraints are detected. MV and LV flexibilities could be used to solve the MV network constraints, provided that they are located and aggregated on the right place Problems addressed Management of congestion of MV network (voltage, current ). Expected benefits Increased flexibility from energy players, improve competitiveness of electricity market, improve the electricity quality Control type Centralised from the DSO point of view and also from the aggregator point of view Control system tools DSO: Planning tools/operational tools (in order to detect the network constraints), SCADA (in order to send the set point to the DG), market platform (in order to receipt and activate the flexibility offers and to ensure the settlement process) Aggregator: communication with the individual flexibilities and also with the DSO through the market platform. Energy boxes or other similar devices installed at each individual flexibility level. Measurement nodes Individual flexibilities Controlled devices Not directly by the DSO, only by the aggregator Solution requirements Existence of aggregator (third parties) in order to optimise the flexibilities portfolio ensuring a communication with the individual flexibilities and also with the DSO through the market platform Risks Liquidity of the market will be not enough to provide the flexibility needed to solve the distribution network constraints. The aggregator is failing and can t provide the flexibility sold. Comments From a regulatory point of view it s necessary to define how the DSO will be cover its costs generated by the economic compensation to be paid to the aggregators for the services provided. Table 72 MV Congestion Management with DG non-firm grid connection contracts V /12/18 70/126

150 5 Annex D: SRA Data collection The approach for the data gathering for the SRA is as follows: DSO Partners are asked to complete the evaluation of all implementations in all scenarios focused on their respective countries. This means that, based on their own experience and knowledge about the distribution networks in their respective countries and the boundary conditions influencing them, they complete the SRA for the following three scenarios: SCN.IGG.01: Scalability in density SCN.IGG.02: Replicability (Today) SCN.IGG.03: Replicability (Future) As a result, the scalability and replicability potential of all implementations is evaluated from the point of view of six different EU countries coinciding with the countries of the DSO Partners involved in the IGREENGrid project (Spain, France, Greece, Italy, Austria and Germany). Specifically, the following surveys have been conducted: Nº DSO Short Name Country 1 ELECTRICITE RESEAU DISTRIBUTION FRANCE ERDF France 2 IBERDROLA DISTRIBUCION ELECTRICA, S.A. IBERDROLA Spain 3 GAS NATURAL FENOSA GNF Spain 4 SALZBURG AG FUR ENERGIE, VERKEHR UND TELEKOMMUNIKATION NETZ OBERÖSTERREICH SAG NetzOÖ 5 ENEL DISTRIBUZIONE S.P.A. ENEL Italy Austria 6 RWE DEUTSCHLAND AKTIENGESELLSCHAFT RWE Germany 7 DIACHEIRISTIS ELLINIKOU DIKTYOU DIANOMIS ELEKTRIKIS ENERGEIAS AE Table 73 List of surveyed DSOs HEDNO Greece The gathered information is afterwards processed and analyzed. On the one side, average scores taking into account the answers from all involved DSOs are calculated to provide a general idea of the replicability and scalability potential of the considered solutions. On the other side, the scores assigned to the different implementations by DSOs from different countries are compared with the aim of finding specific issues from each country that may differ from the general conclusions. These will be mainly related to different regulatory frameworks prevailing; different network status regarding the level of monitoring, the DRES penetration levels. It has to be noted that a little dispersion on the scores provided by different countries is normal due to the slight variations on the criteria employed by the experts when completing the survey. Table 74 includes the functionalities that have been considered for the SRA. This list, together with the list of implementations included in each of them represent inputs to T4.2. They have been identified as a result of the qualitative analysis of the solutions carried out in a previous task of the project. V /12/18 71/126

151 Nº Functionality 1 MV Voltage Monitoring 2 LV Voltage Monitoring 3 MV Voltage Control 4 LV Voltage Control 5 MV Congestion Management Table 74 Functionalities considered for the SRA V /12/18 72/126

152 5.1 ERDF (France) Solutions Scalability in density Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) MV Voltage Control MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG MV Centralized (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG LV Voltage Control LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with DG LV Distributed Voltage Control with OLTC, DG LV Distributed (field measurements) Voltage Control with OLTC, DG MV Congestion Management MV Congestion Management with DG non-firm grid connection contracts ( MV Congestion Management with Use of Flexibility (DG, DSM, STR...) Table 75 SRA data for ERDF (France) Scenario: Scalability in density V /12/18 73/126

153 Solutions Replicability (Today) Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) MV Voltage Control MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG MV Centralized (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG LV Voltage Control LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with DG LV Distributed Voltage Control with OLTC, DG LV Distributed (field measurements) Voltage Control with OLTC, DG MV Congestion Management MV Congestion Management with DG non-firm grid connection contracts ( MV Congestion Management with Use of Flexibility (DG, DSM, STR...) Table 76 SRA data for ERDF (France) Scenario: Replicability (Today) Solutions Replicability (Future) Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) MV Voltage Control MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG MV Centralized (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG LV Voltage Control LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with DG LV Distributed Voltage Control with OLTC, DG LV Distributed (field measurements) Voltage Control with OLTC, DG MV Congestion Management MV Congestion Management with DG non-firm grid connection contracts ( MV Congestion Management with Use of Flexibility (DG, DSM, STR...) Table 77 SRA data for ERDF (France) Scenario: Replicability (Future) V /12/18 74/126

154 5.2 IBERDROLA (Spain) Solutions Scalability in density Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) LV Voltage Monitoring LV Voltage Monitoring (AMI) MV Voltage Control MV Distributed Voltage Control with OLTC ,5 MV Distributed Voltage Control with OLTC, DG ,5 MV Centralised (field measurements) Voltage Control with OLTC , MV Supervised (field measurements) Voltage Control with OLTC & DG , MV Supervised Voltage Control with OLTC & DG MV Centralized (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG ,5 4 LV Voltage Control LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with DG LV Distributed Voltage Control with OLTC, DG LV Distributed (field measurements) Voltage Control with OLTC, DG MV Congestion Management MV Congestion Management with DG non-firm grid connection contracts ( MV Congestion Management with Use of Flexibility (DG, DSM, STR...) Table 78 SRA data for IBERDROLA (Spain) Scenario: Scalability in density V /12/18 75/126

155 Solutions Replicability (Today) Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) LV Voltage Monitoring LV Voltage Monitoring (AMI) MV Voltage Control MV Distributed Voltage Control with OLTC ,5 MV Distributed Voltage Control with OLTC, DG ,5 MV Centralised (field measurements) Voltage Control with OLTC , MV Supervised (field measurements) Voltage Control with OLTC & DG , MV Supervised Voltage Control with OLTC & DG MV Centralized (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG ,5 4 LV Voltage Control LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with DG LV Distributed Voltage Control with OLTC, DG LV Distributed (field measurements) Voltage Control with OLTC, DG MV Congestion Management MV Congestion Management with DG non-firm grid connection contracts ( MV Congestion Management with Use of Flexibility (DG, DSM, STR...) Table 79 SRA data for IBERDROLA (Spain) Scenario: Replicability (Today) Solutions Replicability (Future) Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) LV Voltage Monitoring LV Voltage Monitoring (AMI) MV Voltage Control MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC , ,5 MV Supervised (field measurements) Voltage Control with OLTC & DG ,5 MV Supervised Voltage Control with OLTC & DG ,5 MV Centralized (SE) Voltage Control with OLTC , ,5 MV Centralised (SE & OPF) Voltage Control with OLTC & DG LV Voltage Control LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with DG LV Distributed Voltage Control with OLTC, DG LV Distributed (field measurements) Voltage Control with OLTC, DG MV Congestion Management MV Congestion Management with DG non-firm grid connection contracts ( MV Congestion Management with Use of Flexibility (DG, DSM, STR...) Table 80 SRA data for IBERDROLA (Spain) Scenario: Replicability (Future) V /12/18 76/126

156 5.3 GNF (Spain) Solutions Scalability in density Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) LV Voltage Monitoring LV Voltage Monitoring (AMI) MV Voltage Control MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG MV Centralized (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG Table 81 SRA data for GNF (Spain) Scenario: Scalability in density Solutions Replicability (Today) Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) LV Voltage Monitoring LV Voltage Monitoring (AMI) MV Voltage Control MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG MV Centralized (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG Table 82 SRA data for GNF (Spain) Scenario: Replicability (Today) V /12/18 77/126

157 Solutions Replicability (Future) Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) LV Voltage Monitoring LV Voltage Monitoring (AMI) MV Voltage Control MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG MV Centralized (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG Table 83 SRA data for GNF (Spain) Scenario: Replicability (Future) 5.4 SAG & NETZOÖ(Austria) Solutions Scalability in density Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) LV Voltage Monitoring LV Voltage Monitoring (AMI) MV Voltage Control MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG MV Centralized (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG LV Voltage Control LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with DG LV Distributed Voltage Control with OLTC, DG LV Distributed (field measurements) Voltage Control with OLTC, DG MV Congestion Management MV Congestion Management with DG non-firm grid connection contracts ( MV Congestion Management with Use of Flexibility (DG, DSM, STR...) Table 84 SRA data for SAG & NetzOÖ (Austria) Scenario: Scalability in density V /12/18 78/126

158 Solutions Replicability (Today) Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) LV Voltage Monitoring LV Voltage Monitoring (AMI) MV Voltage Control MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG MV Centralized (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG LV Voltage Control LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with DG LV Distributed Voltage Control with OLTC, DG LV Distributed (field measurements) Voltage Control with OLTC, DG MV Congestion Management MV Congestion Management with DG non-firm grid connection contracts ( MV Congestion Management with Use of Flexibility (DG, DSM, STR...) Table 85 SRA data for SAG & NetzOÖ (Austria) Scenario: Replicability (Today) Solutions Replicability (Future) Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) LV Voltage Monitoring LV Voltage Monitoring (AMI) MV Voltage Control MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG MV Centralized (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG LV Voltage Control LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with DG LV Distributed Voltage Control with OLTC, DG LV Distributed (field measurements) Voltage Control with OLTC, DG MV Congestion Management MV Congestion Management with DG non-firm grid connection contracts ( MV Congestion Management with Use of Flexibility (DG, DSM, STR...) Table 86 SRA data for SAG & NetzOÖ (Austria) Scenario: Replicability (Future) V /12/18 79/126

159 5.5 ENEL (Italy) Solutions Scalability in density Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) LV Voltage Monitoring LV Voltage Monitoring (AMI) MV Voltage Control MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG MV Centralized (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG LV Voltage Control LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with DG LV Distributed Voltage Control with OLTC, DG LV Distributed (field measurements) Voltage Control with OLTC, DG Table 87 SRA data for ENEL (Italy) Scenario: Scalability in density Solutions Replicability (Today) Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) LV Voltage Monitoring LV Voltage Monitoring (AMI) MV Voltage Control MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG MV Centralized (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG LV Voltage Control LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with DG LV Distributed Voltage Control with OLTC, DG LV Distributed (field measurements) Voltage Control with OLTC, DG Table 88 SRA data for ENEL (Italy) Scenario: Replicability (Today) V /12/18 80/126

160 Solutions Replicability (Future) Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) LV Voltage Monitoring LV Voltage Monitoring (AMI) MV Voltage Control MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG MV Centralized (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG LV Voltage Control LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with DG LV Distributed Voltage Control with OLTC, DG LV Distributed (field measurements) Voltage Control with OLTC, DG Table 89 SRA data for ENEL (Italy) Scenario: Replicability (Future) V /12/18 81/126

161 5.6 RWE (Germany) Solutions Scalability in density Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) LV Voltage Monitoring LV Voltage Monitoring (AMI) MV Voltage Control MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG MV Centralized (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG LV Voltage Control LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with DG LV Distributed Voltage Control with OLTC, DG LV Distributed (field measurements) Voltage Control with OLTC, DG MV Congestion Management MV Congestion Management with DG non-firm grid connection contracts MV Congestion Management with Use of Flexibility (DG, DSM, STR...) Table 90 SRA data for RWE (Germany) Scenario: Scalability in density V /12/18 82/126

162 Solutions Replicability (Today) Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) LV Voltage Monitoring LV Voltage Monitoring (AMI) MV Voltage Control MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG MV Centralized (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG LV Voltage Control LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with DG LV Distributed Voltage Control with OLTC, DG LV Distributed (field measurements) Voltage Control with OLTC, DG MV Congestion Management MV Congestion Management with DG non-firm grid connection contracts MV Congestion Management with Use of Flexibility (DG, DSM, STR...) Table 91 SRA data for RWE (Germany) Scenario: Replicability (Today) Solutions Replicability (Future) Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) LV Voltage Monitoring LV Voltage Monitoring (AMI) MV Voltage Control MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG MV Centralized (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG LV Voltage Control LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with DG LV Distributed Voltage Control with OLTC, DG LV Distributed (field measurements) Voltage Control with OLTC, DG MV Congestion Management MV Congestion Management with DG non-firm grid connection contracts MV Congestion Management with Use of Flexibility (DG, DSM, STR...) Table 92 SRA data for RWE (Germany) Scenario: Replicability (Future) V /12/18 83/126

163 5.7 HEDNO (Greece) Solutions Scalability in density Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) LV Voltage Monitoring LV Voltage Monitoring (AMI) MV Voltage Control MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG MV Centralized (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG LV Voltage Control LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with DG LV Distributed Voltage Control with OLTC, DG LV Distributed (field measurements) Voltage Control with OLTC, DG MV Congestion Management MV Congestion Management with DG non-firm grid connection contracts ( MV Congestion Management with Use of Flexibility (DG, DSM, STR...) Table 93 SRA data for HEDNO (Greece) Scenario: Scalability in density V /12/18 84/126

164 Solutions Replicability (Today) Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) LV Voltage Monitoring LV Voltage Monitoring (AMI) MV Voltage Control MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG MV Centralized (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG LV Voltage Control LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with DG LV Distributed Voltage Control with OLTC, DG LV Distributed (field measurements) Voltage Control with OLTC, DG MV Congestion Management MV Congestion Management with DG non-firm grid connection contracts ( MV Congestion Management with Use of Flexibility (DG, DSM, STR...) Table 94 SRA data for HEDNO (Greece) Scenario: Replicability (Today) Solutions Replicability(Future) Nº Functionality Implementation Relevance Assets Requirements Economy Risks Ranking Score Ranking Score Ranking Score Ranking Score Ranking Score 1 MV Voltage Monitoring MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) LV Voltage Monitoring LV Voltage Monitoring (AMI) MV Voltage Control MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG MV Centralized (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG LV Voltage Control LV Distributed Voltage Control with OLTC LV Distributed Voltage Control with DG LV Distributed Voltage Control with OLTC, DG LV Distributed (field measurements) Voltage Control with OLTC, DG MV Congestion Management MV Congestion Management with DG non-firm grid connection contracts ( MV Congestion Management with Use of Flexibility (DG, DSM, STR...) Table 95 SRA data for HEDNO (Greece) Scenario: Replicability (Future) V /12/18 85/126

165 6 Annex E: SRA Results 6.1 SRA for MV Voltage Monitoring implementations Description of implementations Table 96 includes the list of implementations related to MV Voltage Monitoring considered for the study: Nº MV Voltage Monitoring 1 MV Voltage Monitoring (RTU) 2 MV Voltage Monitoring (SE) 3 MV Voltage Monitoring (PLF) Table 96 List of implementations for MV Voltage Monitoring MV Voltage Monitoring (RTU): It is based on transmitting real-time remote measurement from a few critical nodes to the SCADA system located in the distribution control centre. MV Voltage Monitoring (SE): A State Estimation (SE) algorithm calculates the most probable status of the system based on the gathered data from SCADA. The SE requires a larger set of measurements and pseudo-measurements but improves network observability. MV Voltage Monitoring (PLF): It is an off-line calculation. A Probabilistic Load Flow (PLF) algorithm carries out probabilistic predictions of voltage profiles at network buses and feeder power flows based on forecasted demand and generation Assessment of the implementations Relevance In this section, the parameter Relevance is evaluated for the MV Voltage Monitoring implementations presented in Table 961. The idea is to assess the necessity of the solutions in the different scenarios. Real time vs off-line MV Voltage Monitoring The main focus of MV network monitoring is improving the network operation so the DSO can check the real state of the network and react to relief any constraint or supply issue. The aim of the MV network monitoring is then ensuring the voltage statutory limits and the detection and release of possible overloads. MV Voltage Monitoring (PLF) consists of an off line calculation based on the load and generation V /12/18 86/126

166 forecasting processed by the PLF. These measurements help to identify expected problematic situations, like overloads and over-voltages well in advance and schedule the manual interventions (switching) that will avoid these situations. MV Voltage Monitoring (RTU) vs MV Voltage Monitoring (SE) In general terms, SE will provide a complete overview of the system based on a limited number of field measurements. Depending on the number and quality of the field measurements, these can be used directly for Voltage Monitoring. RTU is an alternative to SE that provides less information. Qualitative assessment Table 97 includes the scores assigned to the Relevance parameter for the different MV Voltage Monitoring implementations in the different scenarios. These represent the average values for all participating DSOs. As previously mentioned, monitoring helps to identify the points of the network were problems are found as well as the actual situation of the network. MV Monitoring is also required when managing the LV network: as most of the MV/LV transformers have fixed turn ratios, a proper management of the MV voltage is enough to guarantee that the LV power quality objectives are fulfilled. For the purposes of network operation, real time data is required. Consequently, the scores assigned to the implementations that provide real-time information ( SE and RTU ) are higher than the ones assigned to the implementation including off-line calculations for all scenarios. In addition, the score for the SE is higher than the one assigned to the implementation with RTUs because it provides a more complete vision of the status of the distribution network. In a future scenario (SCN.IGG.03) increasing DRES penetration levels are expected. This may require carrying out network reinforcements for increasing network capacity. In case this option is not economically viable, networks will be operated closer to their limits and as a consequence some type of control over the connected DRES will be required in several occasions for ensuring that power quality limits are always fulfilled. This fact will increase the necessity of monitoring the MV network. The greater the increase in DRES, the greater the relevance for these solutions. As a consequence, the scores assigned to MV Voltage Monitoring implementations are higher than in the current scenario (SCN.IGG.02). MV Voltage Monitoring Relevance assessment (Score) Scalability in density SCN.IGG.01 Replicability (Today) SCN.IGG.02 Replicability (Future) SCN.IGG.03 MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) Table 97 Relevance assessment for MV Voltage Monitoring (Average values) Figure 2 includes a graphical representation of the Relevance assessment carried out by the different DSOs involved in the IGREENGrid project. V /12/18 87/126

167 Figure 1 Relevance assessment for MV Voltage Monitoring (per DSO) Most representative deviations from average values are the following ones: SAG and NETZOÖ (Austria) agree on the previous conclusions but they provide more extreme scores to SE and PLF implementations (SE: 10, PLF: 0). SE is already available at SAG and NETZOÖ. In this case there is no relevance for PLF for optimized operation. State Estimation was implemented to SCADA because load flow calculations have never been performed by operation center. Further in comparison to SE, locally operated systems based on RTUs do support monitoring of voltage for changed topologies (in case of disturbance, maintenance or voltage levels exceeding limits). The vision from ENEL (Italy) differs a bit from the previous general conclusions. The Italian MV network is already monitored and well understood. Traditionally optimisation of network performance and planning is carried out using the existing network monitoring data that is available from the SCADA system. As the complexity of the system, from an operational perspective, increases with an increasing DRES presence, there will be an increased need for more advanced monitoring and forecasting tools. It should be noted that real-time network monitoring using RTU and SE, is also an integral part of some of the MV solutions that are being developed and in some cases, such as network automation, real-time data with a high degree of accuracy, using a high bandwidth communications system with low latency is required. For HEDNO (Greece) all MV Voltage Monitoring solutions are assumed as medium effectiveness solutions as they assist on the network performance monitoring and planning, without any actions of control (compared to other solutions of this deliverable). In the future, considering the complexity of the networks, relevance is expected to be higher Assets The Assets parameter evaluates the (technical) complexity of the different implementations in the different scenarios. In general it is considered that the complexity of solution increases with the following factors: When low voltage elements are involved because of the number of components. When communications are required. Bidirectional communications are more complex to execute than unidirectional ones. When customer facilities are involved in some form. There will be more difficulties if customers are expected to change/adapt their own devices as to provide the DSO some sort of service, paid or not. When either using new technologies, or technologies that are new to the grid. Additional V /12/18 88/126

168 complexity could be expected with solutions which would be described as having a low level of maturity in terms of deployment on distribution networks MV Voltage Monitoring (RTU) vs MV voltage Monitoring (SE) It has to be noted that most of the solutions for MV voltage monitoring are quite simple (i.e. there is not a difficulty in measuring the MV voltage at some intermediate node) but the balance between costs and benefits should justify it and investment budgets cover them. There will not be much difference in terms of complexity between the number of measurements identified as critical nodes for the MV Voltage Monitoring (RTU) from those required for a good state estimation ( MV Voltage Monitoring (SE) ). The higher complexity of the SE application affects only to the DSO owned devices. It is accepted that MV Voltage Monitoring with a few critical nodes may not require the DSO to measure DG installations while a proper SE may need to differentiate generation from loads and some, if not most, DG installations would be required to deploy measurements and communications. MV Voltage Monitoring (PLF) MV Voltage Monitoring (PLF) is the simplest solution as forecasting tools are relatively simple and meter data is considered to be already available for billing purposes. So, neither equipment nor new communications are required. Qualitative assessment The average scores assigned to the different implementations regarding the Assets parameter in each scenario are presented in Table 98. As previously mentioned, the implementation including PLF is the simplest one mainly due to the fact that it does not require the deployment of communications. Although there may be some differences on the amount of required sensors for field measurement and SE, the complexity of both of them in terms of assets is similar. In the future scenario SCN.IGG.03 it seems reasonable to assume that there will be more measurements available and that Distribution Management Systems (DMS) will progressively incorporate advanced functions as the distribution state estimation. So the deployment of MV Voltage Monitoring solutions will be simpler. MV Voltage Monitoring Scalability in density SCN.IGG.01 Assets assessment (Score) Replicability (Today) SCN.IGG.02 Replicability (Future) SCN.IGG.03 MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) Table 98 Assets assessment for MV Voltage Monitoring (Average values) V /12/18 89/126

169 Figure 2 includes a graphical representation of the Assets assessment carried by the different DSOs. Figure 2 Assets assessment for MV Voltage Monitoring (per DSO) Main deviations from the general conclusions are the following ones: From the point of view of SAG, NETZOÖ (Austria), the implementation based on a SE is simpler to be implemented that the one based on RTU because transmission of real time remote measurement data is complex (new device and communication systems have to be installed if the same level of accuracy on the results as the provided one by the SE is desired to be obtained). For SE less measurement data are needed because they have it already deployed and availability of data is less critical. In the case of ERDF (France) RTU is the easiest solution to be implemented because they already have some relevant measurements installed in their network that can be used for voltage monitoring. PLF is the most complex one because there is not available information to feed the system nowadays Requirements In this chapter the requirements for the different MV Voltage Monitoring implementations are evaluated. The objective of this parameter is to identify the most important requirements for the solutions implementation and to provide a qualitative evaluation of the easiness to overcome them. The higher score presents a lower importance of the requirements. MV Voltage Monitoring (RTU) & MV Voltage Monitoring (SE) The main requirement for these two implementations is the availability of an advanced Information and Communication Technology (ICT) infrastructure to transmit real time measurement data and to process it. This is strongly related to the bandwidth requirements of the monitoring system which obviously depends on the number of monitoring points. In addition, this communication infrastructure should address other issues such as open architecture, latency, security (authentication, authorization, accounting ), scalability of the communication channel, flexibility of the deployed communication technology... If this infrastructure is not currently available it is required that its deployment is viable from the economical point of view. So it will be necessary to find a solution that fulfils a minimum set of requirements for ensuring that there are not data congestions and problems with the security of the data but at the same time that the costs are reasonable. The location of the substations will also have an impact on the requirements (i.e. rural areas vs. semi-urban areas). V /12/18 90/126

170 SE has additional requirements compared with RTU related to the need of a high performance algorithm running in real-time and high quality of load data models in order to estimate the voltage profile along the feeders as well as more measurements. Other important requirement applying both implementations is regulatory. It is necessary that DSO has access to DG measurements. Otherwise, complete real-time monitoring cannot be implemented. MV Voltage Monitoring (PLF) MV Voltage Monitoring (PLF) is an off-line calculation. It employs predictions based on historical meter data (previous days) which are already available for billing purposes. Therefore it is not necessary that large amounts of measurement data is transmitted in real-time, reducing as a consequence, the requirements related to the advanced ICT infrastructure. Qualitative assessment As previously commented the implementation with fewer number and importance of requirements is the MV Voltage Monitoring (PLF) as it mainly exploits existing metering data received from already installed metering systems in MV network. The remaining two ones are quite similar in terms of requirements. A slightly lower score has been assigned to SE because of the need of a high performance algorithm running in real-time and likely more measurement data for performing a good estimation. In the future, it is expected that several of those requirements will have been reduced so the assigned scores are a bit higher in this scenario. These are presented in Table 99. MV Voltage Monitoring Requirements assessment (Score) Scalability in density SCN.IGG.01 Replicability (Today) SCN.IGG.02 Replicability (Future) SCN.IGG.03 MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) Table 99 Requirements assessment for MV Voltage Monitoring (Average values) Figure 3 includes a comparison of the scores assigned by the different DSOs to the different implementations regarding the Requirements parameter. Figure 3 Requirements assessment for MV Voltage Monitoring (per DSO) V /12/18 91/126

171 The most relevant differences correspond to ERDF (France) and SAG, NETZOÖ (Austria) For ERDF (France) the PLF is the implementation with higher number and importance of requirements in the current two scenarios. As previously commented this is because there is not available information to feed the system nowadays. However, it is expected to diminish them in the future scenario. For SAG, NETZOÖ (Austria), PLF is given a score of 10 meaning that it has no requirements for their implementation compared to detailed network planning Economy This chapter includes an assessment of the economic viability of deploying the different MV Voltage Monitoring implementations. MV Voltage Monitoring (RTU) & MV Voltage Monitoring (SE) These two implementations require the deployment of an advanced communication infrastructure for transmitting real time measurement data. If this is not already available it can represent a high investment cost that can make the solutions unviable from the economic point of view. The cost associated to the MV Voltage Monitoring (SE) implementation is a bit higher due to the state estimation application and the higher number of measurements. MV Voltage Monitoring (PLF) MV Voltage Monitoring (PLF) is the less complex solution in terms of assets and therefore it is the most economical one because neither equipment nor new communications are required. Qualitative assessment The scores assigned to the different implementations regarding the Economy parameter in each scenario are presented in Table 100. As previously mentioned, the implementation including PLF is the simplest one in terms of economy as it is based on software and it exploits existing metering data and communications. The remaining two ones are quite similar in terms of assets and therefore in terms of costs. A slightly lower score is given to SE in relation to field measurement because it also needs licences and hardware to implement the state estimation algorithm and the higher number of measurements needed. Economy assessment (Score) MV Voltage Monitoring Scalability in density SCN.IGG.01 Replicability (Today) SCN.IGG.02 Replicability (Future) SCN.IGG.03 MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) Table 100 Economy assessment for MV Voltage Monitoring (Average values) V /12/18 92/126

172 Figure 4 includes the evaluation made by the different DSOs of the Economy parameter for the different implementations. Figure 4 Economy assessment for MV Voltage Monitoring (per DSO) Main differences from general conclusions are the following ones: ENEL (Italy) agrees on the previous conclusions but it has assigned higher scores than the other DSOs to all implementations. This is because it has considered that communications network with sufficient bandwidth exists (or is being developed as part of another solution). ERDF (France) differs from the previous conclusions. From their point of view, the PLF is the most costly implementation because the AMI infrastructure is not deployed nowadays in their networks. In addition, AMI in France doesn t allow to measure voltage in real time, it s not adapted to implement this kind of solution. They do not already have any measurements at the secondary substation level and MV customers are metered only once per month for billing purposes Risks In this chapter a qualitative assessment of the risks impacting the MV Voltage Monitoring implementations is carried out. The higher the score presents a lower impact of the risks on the solution. MV Voltage Monitoring (RTU) & MV Voltage Monitoring (SE) A risk associated to the MV Voltage Monitoring implementations that require real time communications ( RTU and SE ) is related to the failure of the communication channels (e.g. saturation). If this happens, data is not exchanged with the required frequency and as a consequence control solutions that require real time measurement data cannot be applied. This is the case for example of centralised Voltage Control solutions. It is more likely that this happens in remote areas. A critical issue related to the communication infrastructure is security of data. Customer information is confidential and therefore the communication system has to be designed to ensure privacy of data. This might require encryption. However, develop secure communication channels that avoid cyber security threats and attacks can increase highly the costs of communications. Regarding this topic standardization of communication protocols is also required. Another risk is the standardization of technologies. In the case of Monitoring this is mainly related to the metering devices. Each manufacturer has its own devices that include a different set of functionalities and implement different communication protocols. Consequently, integration of them might require a high amount of technical and economic resources to develop dedicated components. In fact, even when all smart meters implement the same protocol (e.gs Modbus) there V /12/18 93/126

173 can be problems for the integration because it is an open protocol that does not fix the language that the devices should speak. So a risk to large scale deployment of the solution is the standardization of communications. RTU has an associated risk in case of switching operations because the network topology could vary so the selection of the critical nodes may not fully reflect the new critical nodes. Finally, a regulatory risk exists regarding the access to DG data. For the implementation of these solutions it is necessary that DSO is allowed to access real-time measurement data. MV Voltage Monitoring (PLF) MV Voltage Monitoring (PLF) is mostly an off-line calculation that requires real time measurement data only at the HV substation, so the risks related to the communications diminish. The remaining risks are similar to the ones mentioned for the previous two implementations. Qualitative assessment The risks assessment (Table 101) shows that the implementation with lower number and importance of risks is MV Voltage Monitoring (PLF). Risks for the other two solutions are quite similar, including mainly communications and standardization problems. The average scores assigned to the future scenario (SCN.IGG.03) are higher because it is considered that a high effort on standardization of communication protocols and smart grid components will be carried out in the coming years and therefore the risks related to these issues will be mostly mitigated. MV Voltage Monitoring Scalability in density SCN.IGG.01 Risks assessment (Score) Replicability (Today) SCN.IGG.02 Replicability (Future) SCN.IGG.03 MV Voltage Monitoring (RTU) MV Voltage Monitoring (SE) MV Voltage Monitoring (PLF) Table 101 Risks assessment for MV Voltage Monitoring (Average) Figure 5 includes the evaluation carried out by the different DSOs of the Risks parameter. Figure 5 Risks assessment for MV Voltage Monitoring (per DSO) The most representative differences are the following ones. V /12/18 94/126

174 For ENEL (Italy) the risks impacting all MV Voltage Monitoring solutions are very low (very high scores assigned). The main risk would be brief interruptions of communications in some remote areas. The impact is dependent on requirements but if used for providing data for operation/planning then very brief interruptions are not expected be that critical. A lower latency would also be more acceptable. SAG, NETZOÖ (Austria) considers that RTU has more risks than SE. In fact, a score of 0 is given to this implementation in all scenarios. If field measurements are used for operational purpose the change of topology is linked to a high risk. If resulting voltages are not estimated before switching this way of operation can be understood as experimental. For ERDF (France) the risks related to PLF are very high. This is because AMI infrastructure is not deployed nowadays in their networks. These are expected to be highly reduced in the future. 6.2 SRA for LV Voltage Monitoring implementations Description of the implementations Table 102 includes the LV Voltage Monitoring implementation considered in the study. The objective of conducting the SRA over one single solution is aimed to expose the actual needs for LV monitoring and its possible evolution in the future. Nº LV Voltage Monitoring 1 LV Voltage Monitoring (AMI) Table 102 List of implementations for LV Voltage Monitoring LV Voltage Monitoring (AMI): It is an off-line calculation. A process/algorithm analyses the values of voltage measurements recorded by the smart meters Assessment of the implementations Relevance In this section, the parameter Relevance is evaluated for the LV Voltage Monitoring implementation presented in Table 102. The idea is to assess its necessity in the different scenarios. Qualitative assessment Monitoring is aimed to learn about the real situation of the network, real margins, real Quality of Service (QoS) problems, load effects, impact of DRES, etc. In the current scenarios (SCN.IGG.01 and SCN.IGG.02), off-line processing of smart meter data downloaded once a day seems to be good enough for this purpose. The LV side of the secondary substation may be monitored but there is not much gain over the MV side of the transformer unless some other control mechanism is in place for voltage purposes. V /12/18 95/126

175 In a future scenario the necessity of LV Voltage Monitoring will increase in some specific locations probably linked to the necessity of control. LV Voltage Monitoring Relevance assessment (Score) Scalability in density SCN.IGG.01 Replicability (Today) SCN.IGG.02 Replicability (Future) SCN.IGG.03 LV Voltage Monitoring (AMI) Table 103 Relevance assessment for LV Voltage Monitoring (Average values) Figure 6 includes the Relevance assessment carried out for the different DSOs. Figure 6 Relevance assessment for LV Voltage Monitoring (per DSO) Main representative differences are as follows: A comparison among the evaluations made by the different DSOs show that ENEL (Italy) has assigned the maximum score (10) to the relevance of LV Voltage Monitoring (AMI). In fact, ENEL has already deployed an Advanced Metering Infrastructure (AMI) through all of its networks. In the case of France smart meters do not record voltage measurement. This means that this implementation is not feasible in France. Its deployment would require the individual modification of meter parameters and an extensive additional data centres. Due to this reason this implementation has not been evaluated by the French DSO (ERDF). HEDNO (Greece) considers that the necessity of AMI solution is high but applicability is low as implementation is still difficult in Greece. Due to this reason a medium score is assigned. For the future scenario, it is assumed that necessity and applicability will be increased, thus the score is increased Assets The Assets parameter evaluates the (technical) complexity of the deployment of the implementation in the different scenarios. Qualitative assessment In general it can be stated that MV functionalities should be simpler in terms of the assets complexity over those for LV basically because of the number of components required. MV networks are clearly more automated and monitored than LV networks. V /12/18 96/126

176 However, the exception comes for LV Monitoring (AMI) because it is based on off-line processing of smart meter recorded data. Smart meters are being deployed across Europe due to European Commission (EC) recommendation / regulation even if some countries such as Germany have dismissed temporally smart meters deployment because of the negative Cost Benefit Analysis (CBA). So it is a simple solution in terms of assets because processing tools would work on smart meter data. Table 104 includes the assigned average scores to the LV Voltage Monitoring (AMI) implementation. The complexity in terms of assets is the same for all scenarios. LV Voltage Monitoring Scalability in density SCN.IGG.01 Assets assessment (Score) Replicability (Today) SCN.IGG.02 Replicability (Future) SCN.IGG.03 LV Voltage Monitoring (AMI) Table 104 Assets assessment for LV Voltage Monitoring (Average values) The assessment per DSO is shown in Figure 7: Figure 7 Assets assessment for LV Voltage Monitoring (per DSO) Main representative differences are as follows: As previously commented, ENEL (Italy) has already deployed an AMI infrastructure in their networks. Due to this reason, the maximum score is assigned to this implementation. HEDNO (Greece) assigns medium score for the assets of the solution taking into account the amount of meters required for the deployment of the LV monitoring Requirements In this chapter the requirements for the LV Voltage Monitoring (AMI) implementation are evaluated. Qualitative assessment LV Voltage Monitoring does not require the transmission of measurement data in real-time. This information is usually sent once per day. This reduces considerably the technical requirements for the communication infrastructure. The main requirement would be related to the amount of meters required for performing LV Monitoring. The scores assigned to all scenarios are the same. V /12/18 97/126

177 LV Voltage Monitoring Requirements assessment (Score) Scalability in density SCN.IGG.01 Replicability (Today) SCN.IGG.02 Replicability (Future) SCN.IGG.03 LV Voltage Monitoring (AMI) Table 105 Requirements assessment for LV Voltage Monitoring (Average values) A comparison of the scores per DSO shows that all of them are close to the average values and therefore they all find the MV Voltage Monitoring (AMI) a relatively simple solution to be implemented in terms of requirements. Figure 8 Requirements assessment for LV Voltage Monitoring (per DSO) Economy This chapter includes an assessment of the costs related to the LV Voltage Monitoring (AMI) implementation. Qualitative assessment As previously stated for the Assets parameter, LV Voltage Monitoring (AMI) is a simple solution to be deployed because it does not require the real exchange of data diminishing as a consequence the high costs related to the deployment of an advanced communication infrastructure. In addition, it has to be taken into account that smart meters are being deployed across Europe so most of the required infrastructure is already deployed. The assigned scores regarding the Economy parameter in each scenario are presented in Table 106. LV Voltage Monitoring Scalability in density SCN.IGG.01 Economy assessment (Score) Replicability (Today) SCN.IGG.02 Replicability (Future) SCN.IGG.03 LV Voltage Monitoring (AMI) Table 106 Economy assessment for LV Voltage monitoring (Average values) A comparison of the scores assigned by the different DSOs is presented in Figure 9. V /12/18 98/126

178 Figure 9 Economy assessment for LV Voltage Monitoring (per DSO) Main representative differences are as follows: ENEL (Italy) assigns the maximum score because they already have deployed the AMI infrastructure in their networks. HEDNO (Greece) assigns medium score for the economy of the solution taking into account the amount of meters required for the deployment of the LV monitoring. No difference for the future scenario in terms of economy Risks In this chapter a risks assessment for the LV Voltage Monitoring (AMI) implementation is carried out. Qualitative assessment LV Voltage Monitoring based on AMI is normally not performed in real-time and this diminishes the risks associated to the advanced communication infrastructure such as congestion and data security. One important risk for large scale deployment of this solution is the standardization of the devices. If smart meters are not standardized the massive deployment of them could be very costly because integration of different manufacturers equipment requires the development of dedicated solutions because each device may have its own particularities (e.g. communication protocols). This is particularly important for the LV level because of the high number of involved devices. Standardization of smart meters is also necessary for ensuring that the devices that are being installed nowadays are going to fulfil with the requirements that will be asked by the regulation in the future (frequency of data collection, control options allowed ). Otherwise additional investment would have to be carried out for retrofitting them. So it can be stated that standardization is related to the security of investment. The scores assigned to the future scenario (SCN.IGG.03) are higher because it is considered that high efforts on standardization of communication protocols and smart grid components will be carried out and therefore the risks related to these issues will be mostly mitigated. V /12/18 99/126

179 LV Voltage Monitoring Scalability in density SCN.IGG.01 Risks assessment (Score) Replicability (Today) SCN.IGG.02 Replicability (Future) SCN.IGG.03 LV Voltage Monitoring (AMI) Table 107 Risks assessment for LV Voltage Monitoring (Average values) A comparison of the Risks assessment carried out by the different DSOs is presented in Figure 10. Figure 10 Risks assessment for LV Voltage Monitoring (per DSO) The most relevant differences that can be found on the assigned scores are the following ones. ENEL (Italy) assigns the maximum score to this implementation in all scenarios. As previously commented, AMI is already deployed in their networks and therefore there are no risks related to this implementation. Also NetzÖO (Austria) assigns a 10 to this implementation because similarly to ENEL (Italy), AMI is already in a deployment phase with deployment already complete for 40% of their customers. In the current scenarios, the scores assigned by GNF (Spain) are quite low. In GNF, the already deployed smart meters do not support the LV monitoring. They are only used for billing purposes. An important risk to consider is that, if the regulation changes, the devices that are being installed today could be useless in the future. It is remarkable due to the high number of involved devices. HEDNO (Greece) assigns medium scores for the risks of the solution taking into account the amount of meters and the possible risks that may arise during the deployment of the LV monitoring. No difference is found for the future scenario. 6.3 SRA for MV Voltage Control implementations Description of the implementations Table 108 includes the list of implementations for MV Voltage Control considered for the SRA. V /12/18 100/126

180 Nº MV Voltage Control 1 MV Distributed Voltage Control with OLTC 2 MV Distributed Voltage Control with OLTC, DG 3 MV Centralised (field measurements) Voltage Control with OLTC 4 MV Supervised (field measurements) Voltage Control with OLTC & DG 5 MV Supervised Voltage Control with OLTC & DG 6 MV Centralized (SE) Voltage Control with OLTC 7 MV Centralised (SE & OPF) Voltage Control with OLTC & DG Table 108 List of implementations for MV Voltage Control MV Distributed Voltage Control with OLTC: The local control of the primary substation adjusts the turn ration of the HV/MV transformer based on local measurements to maintain desired voltage level at the MV network. MV Distributed Voltage Control with OLTC, DG: This solution is based on the conventional management of the OLTC of the HV/MV transformer adding a local control mechanism at MV DGs so reactive power injection is adjusted depending on the local voltage. MV Centralised (field measurements) Voltage Control with OLTC: This approach improves the control of the transformer OLTC at the HV/MV substation by adding remote measurements from some critical nodes of the MV network. The control is triggered when some of the sensed voltages are out of the statutory limits bringing the MV voltage levels back within the threshold. MV Supervised (field measurements) Voltage Control with OLTC & DG: The solution is based on a distributed control placed at the HV/MV substation. The control algorithm manages the HV/MV transformer OLTC based on field measurements from the MV to ensure that MV voltage level is adequate and is also able to issue reactive power commands to MV DGs when needed. MV Supervised Voltage Control with OLTC & DG: This implementation is based on a central SCADA system receiving filed measurements and alarms. Under normal operation, MV DGs adapt their reactive power injection to the local conditions of the grid and send an alarm when reaching their limit. A centralized algorithm adjusts the HV/MV transformer OLTC and the reactive power provision from the remaining MV DGs as to satisfy the expected quality of supply target. MV Centralized (SE) Voltage Control with OLTC: This implementation employs a SE to build a reliable snapshot of the MV network situation and issues control orders to modify the turn ration of the HV/MV transformer through the OLTC tap if needed. The distribution SE runs over the measurements acquired by the central SCADA system. MV Centralised (SE & OPF) Voltage Control with OLTC & DG: This is the most complex solution in terms of tools. The DMS includes a distribution SE to calculate a network image used latter on to feed an OPF on charge of solving any network constraint and defining the set of actions V /12/18 101/126

181 as to achieve some objective function (e.g. losses reduction, minimization of reactive power ). The set of conventional network elements used to manage MV voltage levels (HV/MV transformer OLTC, capacitor banks ) is widened as to include the reactive power support from MV DGs Assessment of the implementations Relevance This chapter is focused on analysing the necessity of MV Voltage Control solutions in the different scenarios. Up to now, distribution networks have been planned for the worst case conditions and these leads to secure operation under the remaining conditions because the DSO may be conveniently sure that power quality requirements are being fulfilled. Smart grid solutions represent an alternative to the conventional grid reinforcement. For old networks (e.g. more than 40 years), reinforcement will be always the best solution because retrofitting the grid with the required components for the development of smart grid solutions would not be technically or economically viable (e.g. deployment of the required communication infrastructure). So, this kind of solutions would be more applicable in new or recently reinforced grids where voltage problems could arise as consequence of increasing levels of DRES. Qualitative assessment Table 109 includes the assessment carried out for the MV Voltage Monitoring implementations. In general, centralised solutions receive the higher scores because they are considered to contribute to solve more important voltage control constraints. These are followed by distributed solutions because of their simplicity and economic viability. In the future (SCN.IGG.03), the need of MV Voltage control solutions will increase with DRES penetration. V /12/18 102/126

182 MV Voltage Control Relevance assessment (Score) Scalability in density SCN.IGG.01 Replicability (Today) SCN.IGG.02 Replicability (Future) SCN.IGG.03 MV Distributed Voltage Control with OLTC MV Distributed Voltage Control with OLTC, DG MV Centralised (field measurements) Voltage Control with OLTC MV Supervised (field measurements) Voltage Control with OLTC & DG MV Supervised Voltage Control with OLTC & DG MV Centralised (SE) Voltage Control with OLTC MV Centralised (SE & OPF) Voltage Control with OLTC & DG Table 109 Relevance assessment for MV Voltage Control (Average values) A comparison of the Relevance assessment carried out by the different countries is presented in Figure 11. Figure 11 Relevance assessment for MV Voltage Control (per DSO) Looking at the graphics it can be seen that there exists quite a high dispersion on the assigned scores. The evaluations that differ more from the average conclusions are the following ones: ENEL (Italy) considers that Distributed solutions ( MV Distributed Voltage Control with OLTC and MV Distributed Voltage Control with OLTC, DG ) are the most relevant ones due to their simplicity and economic viability. In a future scenario centralised control may be also necessary given higher levels of DRES. From the point of view of ERDF (France), voltage constraints caused by DG connected to non-dedicated feeders could be solved via distributed solutions while the voltage constraints caused by DG connected to dedicated feeders would require centralised solutions with SE and DG control. HEDNO (Greece) has considered for the evaluation that the current regulatory framework in Greece does not permit DG control. Thus, all the solutions with OLTC have been ranked V /12/18 103/126