CIM for data exchange within a DMS for electric distribution networks. Giulia Troglio, Federico Silvestro

Transcription

1 for data exchange within a DMS for electric distribution networks Giulia Troglio, Federico Silvestro Users Group Spring 203 Meeting

2 Outline The SmartGen Project Project Architecture The adoption of Testing Phase Conclusion 2

3 Outline The SmartGen Project Project Architecture The adoption of Testing Phase Conclusion 3

4 SmartGen Project Title Study, development and validation of methodologies and tools for the management of active power distribution networks including renewable energy sources Foundings Funded by MISE (Italian Ministry for Economic Development) in the context of the Research Projects for the Electric Systems Context: Smart Grids Operation of generators of any size and technology Load active role in the optimization of operation Availability of more information and wider choice of suppliers Reduction of environmental impact Enhancement of reliability, security and quality of service Image published in Consumer Energy Report All rights reserved 4

5 Active Power (pu) Autumn Load Profiles Residential Agricultural Industrial Commercial Time (h) Project Consortium University of Genova - DINAEL Scientific coordinator DMS architecture, technology survey and enhancement, dissemination University of Bologna - DIE DMS advanced functionalities and monitoring interfaces Academic research Softeco Sismat S.r.l. Project coordination System integration, automation and communication software, wholesale market management s.d.i. S.p.A. SCADA & DMS design and implementation, innovative power network management Industrial research Enel Engineering and Research System requirements, DMS architecture definition, piloting and demonstration Industrial infrastructure research START: January 20 DURATION: 36 months COSTS > 2.8 M Financing =. M

6 SmartGen Project Role WHOLESALE ELECTRIC MARKET. ENERGY BALANCE Generation / Demand Load curve control 2. GRID SECURITY Network stability Provision continuity / QoS POWER GRID INFRASTRUCTURE Transmission & distribution network Microgrid, VPP/VPU 6

7 Project Objectives Analyzing scenarios of Smart Grids and active interaction with the electricity market Distributed Generation (DG) and storage Possibility of load control To identify main technical and economical constraints To define future actors (aggregators, price signals, active demand management) Defining and implementing the architecture of an innovative DMS (Distribution Management System) Interface to data acquisition and SCADA (Supervisory Control And Data Acquisition) systems State estimation and simulation scenarios Management of optimization problems, control of power flow, voltage and supply of ancillary services from DG, and load dispatch Study of different distribution management modes: normal (system interconnected to the main distribution network), dysfunctional, and/or emergency mode (islanding) Demonstrating features and benefits in a real use case Definition of complex reference scenarios Validation of real network functional efficiency Integration of real networks and simulation in pilot sites 7

8 Outline The SmartGen Project Project Architecture The adoption of Testing Phase Conclusion 8

9 SmartGen Contextualization POWER GRID Transmission Distribution (MT/BT) Microgrid Virtual Power Plant Virtual Power Utility EMS HV networks MARKET Trading Ancillary Service Economical constraints Advanced Functionalities Management Control Forecast Simulation MV/LV networks Technical constraints DMS 9

10 OPC DISTRIBUTION TRANSMISSION COMMUNICATION SCADA SERVICE BROKER / SCHEDULER COMMUNICATION SCADA Architecture - details TECHNICAL CONSTRAINTS (INFRASTRUCTURE) ECONOMICAL CONSTRAINTS (MARKET) HV EMS ACTIVE DEMAND / DSM TRADING LOAD/PRODUCTION AGGREGATION ANCILLARY SERVICES HV/MV MV DECENTRALIZED CONTROL GENERATION STORAGE FAULT LOCATION LOCAL CONTROL LOCAL CONTROL ADVANCED FUNCTIONALITIES (ALGORITHMS) LOAD FORECAST GENERATION FORECAST LOAD LOCAL CONTROL STATE ESTIMATION MV/LV DECENTRALIZED CONTROL FAULT LOCATION OPTIMIZATION OPTIMAL RECONFIGURATION GENERATION LOCAL CONTROL FAULT LOCATION LV STORAGE LOCAL CONTROL SERVER I/O LOAD LOCAL CONTROL TECHNICAL CONSTRAINTS (ELECTRICAL NETWORK) REAL TIME DB HISTORIAN DB DB TECHNICAL CONSTRAINTS (SIMULATION) SmartGen DMS 0

11 OPC DISTRIBUTION TRANSMISSION COMMUNICATION SCADA SERVICE BROKER / SCHEDULER COMMUNICATION SCADA 2. Decentralized TECHNICAL CONSTRAINTS (INFRASTRUCTURE) control HV EMS Architecture control levels ECONOMICAL CONSTRAINTS (MARKET). Central control TRADING ACTIVE DEMAND / DSM ANCILLARY SERVICES LOAD/PRODUCTION AGGREGATION HV/MV MV DECENTRALIZED CONTROL GENERATION STORAGE FAULT LOCATION LOCAL CONTROL LOCAL CONTROL ADVANCED FUNCTIONALITIES (ALGORITHMS) LOAD FORECAST GENERATION FORECAST (weather) LOAD LOCAL CONTROL STATE ESTIMATION MV/LV DECENTRALIZED CONTROL FAULT LOCATION OPTIMIZATION OPTIMAL RECONFIGURATION GENERATION LOCAL CONTROL FAULT LOCATION LV STORAGE LOCAL CONTROL SERVER I/O LOAD TECHNICAL CONSTRAINTS (ELECTRICAL NETWORK) 3. Local control TECHNICAL CONSTRAINTS (SIMULATION) LOCAL CONTROL REAL TIME DB HISTORIAN DB DB SmartGen DMS

12 SmartGen DMS based on SCADA system, for data acquisition from the field Server, as an archive for data Advanced DMS component, with smart features Communication among DMS components: Data exchange on a regular basis Periodically Upon request DMS Communication Each system based on its own proprietary format to Read input data Store information Write output data Need for a universal model for data structure Data exchange among the DMS components Connection to external systems 2

13 Outline The SmartGen Project Project Architecture The adoption of Testing Phase Conclusion 3

14 Adopting the constitutes Common language enabling information exchange Universal model providing interoperability It implies the development of Conversion module From to the SCADA proprietary format and vice versa From to the advanced-component proprietary format and vice versa -data retrieve functionalities -based DMS able to Integrate further -based applications, with no additional implementation Being interfaced with external -based SCADAs or DMSs Communicate with any other external -based system 4

15 versions in SmartGen v4 ENTSO-E 2009 (as exported by DIgSilent) SmartGen profile includes: Elements represented by the SCADA Elements of the advanced DMS component Standard IEC6970 Core OperationalLimits Topology Wires Generation Production LoadModel Meas SCADA ControlArea StateVariables Standard IEC 6968 extensions Electric Market interface SmartGen Profile 5

16 Communication Architecture SERVICE BROKER / SCHEDULER Middleware GIPE GIPE2 interpreter SCADA Power grid Distribution (MV/LV) RDF SERVER data filing ENTSO 2009 v4 <network>_eq.: equipment <network>_sv.: system variables <network>_tp.: topology DB MAT2 interpreter MAT ADVANCED FUNCTIONALITIES LOAD FORECAST GENERATION FORECAST STATE ESTIMATION OPTIMIZATION OPTIMAL RECONFIGURATION FAULT LOCATION 6

17 Input EQ. TP. MS. Topology Equipment Measurements 2MAT interpreter :Topology :Equipment :Measurement MAT ADVANCED FUNCTIONALITIES LOAD FORECAST GENERATION FORECAST STATE ESTIMATION OPTIMIZATION OPTIMAL RECONFIGURATION FAULT LOCATION DMS Features - I/O Output MAT MAT2 interpreter :Measurement : StateVariable Estimated measurements Set points Commands Conversion module 2MAT From to the advanced DMS component proprietary format MAT2 From the advanced DMS component proprietary format to 7

18 Input EQ. TP. MS. Topology Equipment Measurements 2MAT interpreter :Topology :Equipment :Measurement MAT ADVANCED FUNCTIONALITIES LOAD FORECAST GENERATION FORECAST STATE ESTIMATION OPTIMIZATION RECONFIGURATION FAULT LOCATION DMS Features - I/O Output MAT MAT2 interpreter :Measurement : StateVariable Estimated measurements Set points Commands Conversion module 2MAT From to the advanced DMS component proprietary format MAT2 From the advanced DMS component proprietary format to 8

19 DMS Features - I/O Input :Topology :Equipment :Measurement FUNCTIONALITY Output Estimated measurements State variables 2MAT interpreter MAT STATE ESTIMATION MAT MAT2 interpreter class StateVariables : StateVariable class Meas :Measurement Sv Inje ction + pnetinjection: A ctivepower [] + qnetinjection: Re activepower [] Sv Voltage + angle: AngleRadians [] + v: Voltage [] IdentifiedObject Topology:: TopologicalNode Core::Terminal StateVa riable Sv PowerFlow + p: ActiveP ower [] + q: Reactive Power [] IdentifiedObject + connected: B oolean [] + sequencenumber: Integer [] Sv Status + inservice: B oolean [] Sv TapStep + continuouspositio n: Float [] + position: In teger [] PowerSystemResource Wires::TapChanger Equipment Core:: ConductingEquipment IdentifiedObject Core::Terminal +Terminal +Measurements Measurement IdentifiedObject + measurementtype: String [] Disc rete + maxvalue: In teger [] + minvalue: In teger [] + normalvalue: Integer [] Analog + maxvalue: Float [] + minvalue: Float [] + normalvalue: Float [] + positiveflowin: Boolean [] +MeasurementValueSource MeasurementValue IdentifiedObject + sensoraccuracy: PerCent [] + timestamp: AbsoluteDateTime [] AnalogValue + value: Float [] IdentifiedObject MeasurementValueSource DiscreteValue + value: Integer [] 9

20 DMS Features - I/O Input :Topology :Equipment :Measurement FUNCTIONALITY Output Generation set points Generation profiles 2MAT interpreter MAT OPTIMIZATION MAT MAT2 interpreter class Control : SetPoint class SetPoints :RegulationSchedule Core::Unit Measurement ControlType Control IdentifiedObject Meas::Control ConductingEquipment Wires::RegulatingCondEq..* Wires::SynchronousMachine Wires::TapChanger IdentifiedObject Core::PowerSystemResource Wires:: VoltageControlZone Analog SetP oint Disc rete Command..* ValueAliasSet ValueToAlias «enumeration» Wires:: RegulatingControlModeKind «enum» voltage activepower reactivepower currentflow fixed admittance timescheduled temperature powerfactor IdentifiedObject Core::Terminal Wires::RegulatingControl + discrete: Bo olean [] + mode: RegulatingCon trolmodekind [] + targetrange: Float [] + targetvalue: Float [] SeasonDayTypeSchedule Wires::RegulationSchedule 20

21 DMS Features - I/O Input :Topology :Equipment :Measurement FUNCTIONALITY Output Commands Open/close 2MAT interpreter MAT (RE-)CONFIGURATION MAT MAT2 interpreter class StateVariables : StateVariable : Measurement : Command class Control StateVa riable PowerSystemResource Wires::TapChanger Core::Unit ControlType Sv Inje ction + pnetinjection: A ctivepower [] + qnetinjection: Re activepower [] Sv TapStep + continuouspositio n: Float [] + position: In teger [] Measurement Control IdentifiedObject Topology:: TopologicalNode Sv Voltage + angle: AngleRadians [] + v: Voltage [] Core::Terminal Sv PowerFlow + p: ActiveP ower [] + q: Reactive Power [] IdentifiedObject + connected: B oolean [] + sequencenumber: Integer [] Sv Status + inservice: B oolean [] Equipment Core:: ConductingEquipment Analog SetP oint Disc rete Command..* ValueAliasSet ValueToAlias 2

22 Outline The SmartGen Project Project Architecture The adoption of Testing Phase Conclusion 22

23 Software Testing Phase Testing Phases Simulation of data exchange within the SmartGen DMS Using DIgSilent simulator Cigré DER extended Simulated Network SCADA 2 MAT MAT 2 State Estimation DMS Field Testing Phase SmartGen DMS in real networks Italian experimental areas Italian distribution network Real Network SCADA 2 MAT MAT 2 All DMS Functionalities 23

24 + - CH P + - Software Testing Phase Simulated Network Simulated Network SCADA EQ. TP. MS. 2 MAT TR_0_2 2 Com 2 Res Com 4 Res 4 8 Res 8 PV 8 7 Com 7 Wind 7 6 Res 6 PV 6 SV. MS.xm MAT 2 State Estimation H V 0 TR_0_ Feeder 2 I V Feeder I Com Res 2 Com 3 3 Res 3 Com 3 PV 3 4 S S3 PV 4 Res 4 5 PV Res H 2 O 2 Res 5 PV 5 S2 0 FuelCell 5 H 2 O 2 Res 0 Com 0 FuelCell 0 PV 0 Battery 0 9 H 2 O 2 Res 9 Com 9 FuelCell 9 PV 9 Diesel 9 Allocated measures V Battery 5 Measurements

25 Field Testing Phase Real Networks The ensemble of pilot sites was chosen in order to test (in simulated and/or in field) all the SmartGen functions: State estimation Load/generation forecast Optimization of the working point Optimal (re-)configuration Fault location Three sites are identified sites because: They allow to apply and test a comprehensive combination of the DMS functions They already have a good degree of instrumentation More activities aimed at the installation of additional instrumentation will be possible Distribution netwotk AMAIE SpA (Sanremo) Experimental Area ENEL I&R (Livorno) Microgrid University of Genova (Genoa) 25

26 - Experimental Area in Livorno - ENEL Area owned by ENEL INGEGNERIA e RICERCA Internal network MV and LV: Common services and utilities(300kw) Pilot plants for combustion testing (900kW): Experimental plants with distributed generation (200 kw) Experimental storage systems (00 kw) LOAD GENERATION STORAGE Possibility of field tests with no impact on the distributor Functionalities that can be demonstrated State estimation Optimization Islanding 26

27 2 - Sanremo distribution network - AMAIE The portion of the electricity distribution network managed by AMAIE SpA covers about half of Sanremo s municipal area and includes both urban and rural areas The network is composed of A primary substation (HV/MV 32/5 kv) double bar structure equipped with 2 transformers of 40 MVA. 0 MV feeders, typically managed in a radial structure, departing from the substation 5 km of MV lines, both cables and overhead lines. MV network managed in compensated neutral ~ 200 secondary substations (MV/LV 5/0,4 kv), among public and private ones Of which about 0% remotely controlled ~ users ( for domestic use, 5 for industrial use, other) ~50 PV plants x 470 kw in MV 0 x (0-00kW) in LV Domestic < 6 kw Functionalities that can be demonstrated Open/close control function Fault location State estimation 27

28 Microgrid at a MV/LV substation Photovoltaic plant (20 kwp) Monocrystalline module with 80 Wp. Expected production per year: 24,4 MWh Storage (0kW/2kWh) Lithium battery technology Controllable loads System monitoring and real-time control 3 - VPP - University of Genoa Possibility of field tests with no impact on the distributor Functionalities that can be demonstrated State estimation Optimization Islanding PV Battery Substation Aux Substation Micro SCADA 28

29 Outline The SmartGen Project Project Architecture The adoption of Testing Phase Conclusion 29

30 Conclusion Project advances Providing enabling technologies for active distribution network management Distributed generation / Load control Design and development of an advanced DMS, also open to future scenarios of the electricity market Network control / energy balance The Consortium includes the entire supply chain and integrates the necessary research skills Distributors / Universities / Product and service companies The adoption of Provides the SmartGen DMS with interoperability Allows the integration of -based applications, with no additional implementation Enables to interface the SmartGen DMS with external -based systems, without restricted access SmartGen contributes to Diffusion of as a commonly recognized standard for electrical data representation Extension of for the application to distribution network 30

31 for data exchange within a DMS for electric distribution networks Dr. Giulia Troglio Softeco Sismat S.r.l. giulia.troglio@softeco.it Dr. Federico Silvestro Università di Genova federico.silvestro@unige.it info@smartgen.it

32 TR_0_2 CHP Simulated Test Network 2 Com 2 Res Com 4 Res 4 8 Res 8 PV 8 7 Com 7 Wind 7 6 Res 6 PV 6 Allocated measures Measurements V I Feeder 2 Com 3 3 S S2 0 9 Res 9 HV Feeder 2 Res 3 Com 3 PV Res Res 0 Com 0 H 2 O 2 FuelCell 0 H 2 O 2 Com 9 FuelCell 9 TR_0_ I 4 S3 PV 0 PV 9 5 Com Res 5 Battery 0 Diesel 9 0 Res PV 3 PV 4 Res 4 H 2 O 2 FuelCell 5 PV 5 V Battery 5