Grid Analytics Conference 2013

Transcription

1 Grid Analytics Conference 2013 SCADA Data: Breaking down silo-based operations and teams to leverage SCADA data and improve network operation, maintenance and investment decisions Aurélio Blanquet, EDP Distribuição London, 24 th October 2013

2 Agenda 1. EDP and EDP Distribuição in brief 2. EDP Distribuição Big Data Challenge 3. EDP Distribuição Big Data Approach 2

3 Agenda 1. EDP and EDP Distribuição in brief 2. EDP Distribuição Big Data Challenge 3. EDP Distribuição Big Data Approach 3

4 From a local electricity incumbent to a global energy player with a strong presence in Europe, Brazil and considerable investments in the USA #1 World leader Electric Sector in Dow Jones Sustainability Indexes #3 World wind energy company #1 Europe hydro project (+3,5 GW under development) #1 Portugal industrial group United Kingdom 21 Employees USA/ Canada 260 Employees Installed Capacity (MW) Net Generation (GWh) 100% Generation from renewable sources USA Canada Portugal Brazil UK Spain France Belgium Italy Poland Romania China 中国 Poland/ Romania 51 Employees 475 Installed Capacity (MW) 621 Net Generation (GWh) 100% Generation from renewable sources Brazil Employees Electricity Customers Installed Capacity (MW) Net Generation (GWh) 100% Generation from renewable sources Electricity Distribution (GWh) Portugal Angola 7252 Employees Electricity Customers Gas Customers Installed Capacity (MW) Net Generation (GWh) 51% Generation from renewable sources Electricity Distribution (GWh) Gas Distribution (GWh) France/ Belgium 34 Employees 363 Installed Capacity (MW) 705 Net Generation (GWh) 100% Generation from renewable sources Italy 14 Employees Spain Employees Electricity Customers Gas Customers Installed Capacity (MW) Net Generation (GWh) 37% Generation from renewable s Electricity Distribution (GWh) Gas Distribution (GWh)

5 EDP is the #1 in Sustainability

6 The National Electricity System includes EDP Distribuição as the regulated electricity distribution company acting under a public service concession. EDP is also present in the ordinary and special regime generation market and in the regulated and liberalized retail markets Generation Transmission Distribution Commercialization Regulated Concessions Low Voltage Concessions Granted by the 278 Municipalities for a period of 20 years (next concessions are subject to public tender) High/Medium Voltage Concession Granted by the government until 2043 Responsibilities Planning, construction, operation and maintenance of the National Electricity Distribution Network Public lighting investment and maintenance; comercial Comply with Quality of Service and other regulatory requirements Provide market support services (switching, reading, )

7 Quality of Service was significantly improved in the last decade, with average interruption time decreasing more than 85 % Evolution of Time Interruption Equivalent MV (TIE MV) since 2001 TIEPI MV Total excluding extraordinary events; Minutes % Focused investments and increased automation are key levers to improve the quality of supply 99,99% reliability of electric distribution network on 2012 TIEPI MT Time Equivalent to the interruption of the capacity installed in MV/ LV substations

8 Agenda 1. EDP and EDP Distribuição in brief 2. EDP Distribuição Big Data Challenge 3. EDP Distribuição Big Data Approach 9

9 HV and MV remote control and automation investment program leveraged the improvement of QoS in the last decade, leading also to a large increase of events and alarms on the SCADA systems ICT Strategy Quality of Service Operational Efficiency HV/MV Substation Remote Control HV/MV Substation Automation Standard Substation design MV Network Automation Station VHV/HV HV network Substation HV/MV Distribution Network MV network Secondary Substation MV/LV LV network EDP Box Retailer/ Consumer/ Producer WAN LAN HAN Network Assets HV: km 412 HV/MV MV: km MV/LV: km LV Lines Users Level of Monitoring and Automation TODAY Large increase on the SCADA systems available data. 10

10 And under adverse weather conditions we already face the challenge of processing huge amounts of data efficiently and effectively in order to support operational decisions The GONG storm - January 2013, Portugal MV network :00

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18 GONG STORM Damages in EDP network MV network :00 EDP teams recovering network

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31 1,5 millions SCADA events were showed during the Gong storm weekend. The day where Gong storm was more active (19 th January) SCADA system recorded more than 1 million events, almost 8 times more than the homologues day in 2012 SCADA/ DMS events (3 rd week of 2012 vs. 3 rd week of 2013) 246 k k x 7,7 144 k 136 k GONG storm: 1,5 M events 111 k 405 k 319 k 354 k 208 k 220 k 211 k 206 k 198 k 199 k Friday Saturday Sunday Monday Tuesday Wednesday Thursday Major challenges How to deal with a high number of SCADA events in a short period of time? How to process data into reduced, precise and accurate information for decision making? How to predict the impact of storms on the network, timely and accurately? Which mitigation actions can be done to reduce those storm impacts in electrical systems? 2012 (13th to 19th of January) 2013 (18th to 24th of January) 32

32 and in 2010, Xynthia storm had a major impact in TIE contributing with 33 min in a single day, 100 times more that average day TIE TIE evolution (2010; minutes) Xynthia storm 27Feb 1Mar x100 x30 x30 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Legend: TIE TIE day average 33

33 Moreover, the transformation of the energy sector adds new challenges to the DSO, demanding new strategies for the Distribution Power Grid, that becomes progressively more intelligent. Historical Challenges Quality of Service New Challenges Advanced Metering Infrastructure Renewables and Distributed Generation A smarter distribution grid to new challenges New ways of planning and managing the grid (e.g. DG, bidirectional energy flows...) Operational Efficiency Smart Grid Network automation & sensoring More information to customer energy efficiency New technologies (e.g. energy storage) and new business models (e.g. DSM, dynamic energy prices...) EV integration (e.g. V2G, Supply customers with high quality of service Electric vehicle Energy efficiency and new business models smart charging...)... Minimize OPEX and CAPEX 34

34 And to face those new challenges it will we need to increase the visibility over the LV network, reducing the existing gap when compared with HV and MV networks, bringing new challenges towards managing and processing a huge increase of data Station VHV/HV HV network Substation HV/MV Distribution Network MV network Secondary Substation MV/LV LV network EDP Box Retailer/ Consumer/ Producer WAN LAN HAN Network Assets HV: km 412 HV/MV MV: km MV/LV: km LV Lines Users Level of Monitoring and Automation TODAY With SMART GRIDS BIG Valuable DATA Lack of real-time knowledge about the network in this area Impact Decision Making Risk accessement Network operation Investment Network efficiency Risk management Pre-fault detection and location Sel-healing and dynamic reconfiguration RES & DG integration Prosumer experience Demand response Energy efficiency Fault location New services 35

35 Besides this massive increase of data produced by new intelligent devices for monitoring LV, MV and HV network, DSO s need to move forward into a differently interconnected OT and IT systems in order to capture their analytical potential E-Mobility Microgeneration Work Force Management Concentrator SCADA/DMS Smart Meter External Sources HAN devices TSO s SCADA Disaster Recovery Geographic Outage Management Information System System Smart Grid Sources 36

36 Therefore, key challenges will make the most of the available data, creating a new value proposition to boost the power grid operation and the business Performance How can we manage so much data with the proper performance? Integration How can we link data from heterogeneous sources? Knowledge How can we deliver value from data to the business? Security and Privacy How do we ensure security and privacy in this interconnected world? 37

37 Agenda 1. EDP and EDP Distribuição in brief 2. EDP Distribuição Big Data Challenge 3. EDP Distribuição Approach 38

38 Operational risk is evaluated accordingly with the information that it is collected from different sources Symbol Events A maintenance operation in a primary HV/MV substation was scheduled for today afternoon The weather was windy and sunny in the North and rainy in the south There is a strong generation in the north due to RES (sun and wind) SCADA system has the information of normal operation of the electrical network and GIS illustrates HV and MV network typology Source EDM SCADA Low probability of a grid constrain in the south. Maintenance schedule for today afternoon will proceed GIS 40

39 The current sources of information are mostly scattered... Integration of different information sources, internal and external, structured and unstructured have a huge potential to largely improve risk accessment and operations management DISPERSED sources CONNECTED sources Maintenance Mobile operators Meteo Maintenace EDM Meteo Nature Generation & Consumption SCADA EDM Generation & Consumption SCADA 41

40 Improving the impact forecast of external players... when acting in group

41 The integration of information from different sources improve the quality of risk identification Symbol Events A maintenance operation in a primary HV/MV substation was schedule for today afternoon Source SCADA The weather was windy and sunny in the North and rainy in the south There is a strong generation in the north due to RES (sun and wind) SCADA system gives the information of normal operation of the electrical network and GIS illustrates HV and MV network typology A starling was predicted from northeast to southwest for today afternoon Mobile operators are registering a big movement of people from north to south due a Rolling Stones concert in Lisbon EDM Connected sources GIS Situational Awareness 80% possibility of interruption of service in the south region Solution: Delay programmed maintenance 43

42 Utilities are facing new challenges requiring a different approach towards the integration of data sources, processing performance and the volume required to ensure advanced features More Sources and a lot more Data A different Approach 44

43 and systems owners are spread across the organization, leading to an extra interconnection complexity due to its silo based design & different stakeholder business unit s goals Technology SCADA BI SIEM Telecommunications management systems Operations Automation and Telecontrol Dispatching Network Planning Outage Management Management DPLAN Organization Support GIS WFM EPM Commercial Energy Management AMR New Development Projects InovGrid Smart Grids Information Systems Business Support SAP Mail, Internet, Intranet Legend: Area Direction 45

44 Real-time analytics and situational awareness functionalities are becoming the new tools to support stressed network operations, achieving three different levels of maturity with diverse purposes and addressees Grid Now Online Mgmt Leveraging information across systems Grid Intelligence Discovery Mgmt Increase the efficiency of network management Grid Executive Performance Mgmt Integrated view of all operational and non operational information; Leveraging information from endogenous and exogenous systems for the power grid management and decision making; Quick identification Understanding of asset the failures network and root causes. behavior Enhanced decision support through continuous learning, prediction models and pattern behaviors; Anomaly detection proactively and intelligently through alerts with different levels of priority and severity; Timely alert Avoid on asset or decrease stress conditions the time due to endogenous or exogenous conditions. for human intervention in network management Reporting of power grid performance and operational efficiency indicators; Decision support throughout stressed environments; High level observation of all power grid related information in a structured and integrated manner.

45 Utilities must quickly evolve from traditional time and geographical information into this new Einstein's like paradigm of time and space correlation of different events, in different times, on different places, from different structured and unstructured, internal and external data sources Aggregation and correlation of data from various sources (internal and external) Viewing real-time space and time network state in its different forms (e.g. outages) and risks Analysis of current information for historical knowledge and prediction of network behavior Normal Environment What? When? Where? Why? What to do? Stressed Environment Top decision makers and external communication Process responsible and Intermediate Decision Makers Network Operators and Analysts 47 47

46 and a forward looking vision of the use cases that will take most advantage of this platform adding value to the business will facilitate the task of managing such a complex and heterogeneous environment, delivering a comprehensive and timely understanding of the distribution network Voltage Optimization Regulatory Compliance Power Factor Improved Asset Management Non-Interruption Calls

47 Thank you for your attention We will not be limited by the information we have. We will be limited by our ability to process this information (Peter Drucker) Aurélio Blanquet EDP Distribuição 49