cim for data exchange within a dms for electric...

www.smartgen.it

CIM for data exchange within a DMS for electric

distribution networks

CIM Users Group Spring 2013 Meeting

Giulia Troglio, Federico Silvestro

Outline

• The SmartGen Project

• Project Architecture

• The adoption of CIM

• Testing Phase

• Conclusion

2

Outline




• Testing Phase

• Conclusion

3

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

4

Image published in Consumer Energy Report - http://www.consumerenergyreport.com/wp-

content/uploads/2010/04/smartgrid.jpg - All rights reserved

• 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

http://www.consumerenergyreport.com/wp-content/uploads/2010/04/smartgrid.jpg



Project Consortium

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

Enel Engineering and Research System requirements, DMS architecture definition, piloting and demonstration

University of Genova - DINAEL Scientific coordinator DMS architecture, technology survey and enhancement, dissemination

University of Bologna - DIE DMS advanced functionalities and monitoring interfaces

0 24 48 72 96 120 144 1680

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1Autumn Load Profiles

Acti

ve P

ow

er (

pu

)

Time (h)

Residential

Agricultural

Industrial

Commercial

Academic research

Industrial infrastructure research

Industrial research

START: January 2011 DURATION: 36 months COSTS > 2.8 M€

Financing = 1.1 M€

SmartGen Project Role

6

1. ENERGY BALANCE Generation / Demand Load curve control

WHOLESALE ELECTRIC MARKET

POWER GRID INFRASTRUCTURE Transmission & distribution network

Microgrid, VPP/VPU

2. GRID SECURITY Network stability Provision continuity / QoS

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

Outline




• Testing Phase

• Conclusion

8

SmartGen Contextualization

9

DMS

POWER GRID Transmission Distribution (MT/BT)

Microgrid Virtual Power Plant Virtual Power Utility

Technical constraints

MARKET Trading

Ancillary Service

Economical constraints

EMS HV networks

Advanced Functionalities

Management Control

Forecast Simulation

MV/LV networks

Architecture - details

10

TECHNICAL CONSTRAINTS (INFRASTRUCTURE)

TECHNICAL CONSTRAINTS (ELECTRICAL NETWORK)

DIS

TRIB

UTI

ON

TR

AN

SMIS

SIO

N

SCA

DA

ECONOMICAL CONSTRAINTS (MARKET)

MV

LV

GENERATION

STORAGE

LOAD

HV/MV

LOCAL CONTROL

GENERATION

STORAGE

LOAD

EMS HV

CO

MM

UN

ICA

TIO

N

SmartGen DMS

ADVANCED FUNCTIONALITIES (ALGORITHMS)

SER

VIC

E B

RO

KER

/ S

CH

EDU

LER

CIM SERVER

OPTIMAL RECONFIGURATION

STATE ESTIMATION

FAULT LOCATION

OPTIMIZATION

SCA

DA

LOAD FORECAST

GENERATION FORECAST

TECHNICAL CONSTRAINTS (SIMULATION)

HISTORIAN DB

CIM DB

REAL TIME DB

CO

MM

UN

ICAT

ION

ACTIVE DEMAND / DSM

OP

C

LOAD/PRODUCTION AGGREGATION

TRADING

ANCILLARY SERVICES

I/O

LOCAL CONTROL

LOCAL CONTROL

LOCAL CONTROL

LOCAL CONTROL

LOCAL CONTROL

MV/LV DECENTRALIZED CONTROL

FAULT LOCATION

DECENTRALIZED CONTROL

FAULT LOCATION

Architecture – control levels

11

TECHNICAL CONSTRAINTS (INFRASTRUCTURE)

TECHNICAL CONSTRAINTS (ELECTRICAL NETWORK)

DIS

TRIB

UTI

ON

TR

AN

SMIS

SIO

N

SCA

DA

ECONOMICAL CONSTRAINTS (MARKET)

MV

LV

GENERATION

STORAGE

LOAD

HV/MV

LOCAL CONTROL

GENERATION

STORAGE

LOAD

EMS HV

CO

MM

UN

ICA

TIO

N

SmartGen DMS

ADVANCED FUNCTIONALITIES (ALGORITHMS)

SER

VIC

E B

RO

KER

/ S

CH

EDU

LER

CIM SERVER


STATE ESTIMATION

FAULT LOCATION

OPTIMIZATION

SCA

DA

LOAD FORECAST

GENERATION FORECAST (weather)

TECHNICAL CONSTRAINTS (SIMULATION)

HISTORIAN DB

CIM DB

REAL TIME DB

CO

MM

UN

ICAT

ION

ACTIVE DEMAND / DSM

OP

C

LOAD/PRODUCTION AGGREGATION

TRADING

ANCILLARY SERVICES

I/O

LOCAL CONTROL

LOCAL CONTROL

LOCAL CONTROL

LOCAL CONTROL

LOCAL CONTROL

MV/LV DECENTRALIZED CONTROL

FAULT LOCATION

DECENTRALIZED CONTROL

FAULT LOCATION

2. Decentralized control

3. Local control

1. Central control

DMS Communication

• SmartGen DMS based on – SCADA system, for data acquisition from the field

– CIM Server, as an archive for CIM data

– Advanced DMS component, with smart features

• Communication among DMS components: – Data exchange on a regular basis

• Periodically

• Upon request

– 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

12

Outline




• Testing Phase

• Conclusion

13

Adopting the CIM

• CIM constitutes – Common language enabling information exchange

– Universal model providing interoperability

• It implies the development of – Conversion module

• From CIM to the SCADA proprietary format and vice versa

• From CIM to the advanced-component proprietary format and vice versa

– CIM-data retrieve functionalities

• CIM-based DMS able to – Integrate further CIM-based applications, with no additional

implementation

– Being interfaced with external CIM-based SCADAs or DMSs

– Communicate with any other external CIM-based system

14

SmartGen CIM Profile

• CIM versions in SmartGen – CIM v14 ENTSO-E 2009 (as exported by DIgSilent)

• SmartGen CIM profile includes: – Elements represented by the SCADA

– Elements of the advanced DMS component

• Standard IEC61970 – Core

– OperationalLimits

– Topology

– Wires

– Generation • Production

– LoadModel

– Meas

– SCADA

– ControlArea

– StateVariables

• Standard IEC 61968 extensions

• Electric Market interface

15

Middleware

Communication Architecture

16

SCADA

Power grid Distribution (MV/LV)

ADVANCED FUNCTIONALITIES

SERVICE BROKER / SCHEDULER

CIM SERVER CIM data filing

CIM xml CIM

xml CIM xml

ENTSO 2009 CIM v14 <network>_EQ.xml: equipment <network>_SV.xml: system variables <network>_TP.xml: topology

CIM DB

RDF GIPE2CIM interpreter

MAT2CIM interpreter

MAT xml

CIM xml

GIPE xml

CIM xml

CIM xml

CIM xml

CIM xml


STATE ESTIMATION

FAULT LOCATION

OPTIMIZATION

LOAD FORECAST

GENERATION FORECAST

Output Input

DMS Features - I/O

17

CIM2MAT interpreter

MAT xml

MAT2CIM interpreter

MAT xml

CIM xml

• Estimated measurements

• Set points • Commands

CIM:Topology CIM:Equipment

CIM:Measurement

• Topology • Equipment • Measurements ADVANCED FUNCTIONALITIES


STATE ESTIMATION

FAULT LOCATION

OPTIMIZATION

LOAD FORECAST

GENERATION FORECAST

• CIM:Measurement • CIM: StateVariable •…

• Conversion module

– CIM2MAT

• From CIM to the advanced DMS component proprietary format

– MAT2CIM

• From the advanced DMS component proprietary format to CIM

CIM EQ.xml TP.xml MS.xml

Output Input

DMS Features - I/O

18

CIM2MAT interpreter

MAT xml

MAT2CIM interpreter

MAT xml

CIM xml


• Set points • Commands


CIM:Measurement

• Topology • Equipment • Measurements ADVANCED FUNCTIONALITIES

RECONFIGURATION

STATE ESTIMATION

FAULT LOCATION

OPTIMIZATION

LOAD FORECAST

GENERATION FORECAST

• CIM:Measurement • CIM: StateVariable •…

• Conversion module

– CIM2MAT

• From CIM to the advanced DMS component proprietary format

– MAT2CIM

• From the advanced DMS component proprietary format to CIM


Output Input

DMS Features - I/O

19

CIM2MAT interpreter

MAT xml

CIM xml

MAT2CIM interpreter

MAT xml

CIM xml


CIM:Measurement FUNCTIONALITY

STATE ESTIMATION

class Meas

IdentifiedObject

Measurement

+ measurementType: String [0..1]

IdentifiedObject

Core::Terminal

Analog

+ maxValue: Float [0..1]

+ minValue: Float [0..1]

+ normalValue: Float [0..1]

+ positiveFlowIn: Boolean [0..1]

Disc rete

+ maxValue: In teger [0..1]

+ minValue: In teger [0..1]

+ normalValue: Integer [0..1]

IdentifiedObject

MeasurementValue

+ sensorAccuracy: PerCent [0..1]

+ timeStamp: AbsoluteDateTime [0..1]

AnalogValue

+ value: Float [0..1]

DiscreteValue

+ value: Integer [0..1]

IdentifiedObject

MeasurementValueSource

+MeasurementValueSource 1

0..*

1 0..*

1

0..*

+Measurements 0..*

+Terminal 0. .1


• State variables

CIM:Measurement class StateVariables

StateVa riable

Sv Inje ction

+ pNetInjection: ActivePower [0..1]

+ qNetInjection: Re activePower [0..1]

Sv Vol tage

+ angle: AngleRadians [0..1]

+ v: Voltage [0..1]

Sv Status

+ inService: Boolean [0..1]

Sv PowerFlow

+ p: ActivePower [0..1]

+ q: Reactive Power [0..1]

Sv TapStep

+ continuousPositio n: Float [0..1]

+ position: In teger [0..1]

IdentifiedObject

Core::Terminal

+ connected: Boolean [0..1]

+ sequenceNumber: Integer [0..1]

IdentifiedObject

Topology::

TopologicalNode

Equipment

Core::

ConductingEquipment

PowerSystemResource

Wires::TapChanger

0..*1

0..*

0. .1

0. .11

0. .1

1

0. .1

1

0. .11

0. .1

1

CIM: StateVariable

Output Input

DMS Features - I/O

20

CIM2MAT interpreter

MAT xml

CIM xml

MAT2CIM interpreter

MAT xml

CIM xml



OPTIMIZATION

• Generation set points • Generation profiles

class Control

Disc rete Command

ValueAliasSet ValueToAlias

SetPointAnalog

ControlType

Control

Core::Unit

Measurement

0. .1 0. .1

0..*0. .10. .1

0..*

1

1. .*

0. .1

0. .1

10..*

1

0..*

0..*

1

• CIM: SetPoint class SetPoints

IdentifiedObject

Core::Terminal

Wires::TapChanger

ConductingEquipment

Wires::RegulatingCondEq

SeasonDayTypeSchedule

Wires::RegulationSchedule

IdentifiedObject

Meas::Control

Wires::SynchronousMachine

Wires::RegulatingControl

+ discrete: Bo olean [0..1]

+ mode: RegulatingCon trolModeKind [0..1]

+ targetRange: Float [0..1]

+ targetValue: Float [0..1]

IdentifiedObject

Core::PowerSystemResource

«enumeration»

Wires::

RegulatingControlModeKind

«enum»

voltage

activePower

reactivePower

currentFlow

fixed

admit tance

timeScheduled

temperature

powerFactor

Wires::

VoltageControlZone

0. .1

0..*0. .1

0..*

0..*1

0. .1

1. .* 0..*

0. .1

0..*

0. .1

• CIM:RegulationSchedule

Output Input

DMS Features - I/O

21

CIM2MAT interpreter

MAT xml

CIM xml

MAT2CIM interpreter

MAT xml

CIM xml



(RE-)CONFIGURATION

Commands Open/close

class Control

Disc rete Command

ValueAliasSet ValueToAlias

SetPointAnalog

ControlType

Control

Core::Unit

Measurement

0. .1 0. .1

0..*0. .10. .1

0..*

1

1. .*

0. .1

0. .1

10..*

1

0..*

0..*

1

class StateVariables

StateVa riable

Sv Inje ction

+ pNetInjection: ActivePower [0..1]

+ qNetInjection: Re activePower [0..1]

Sv Vol tage

+ angle: AngleRadians [0..1]

+ v: Voltage [0..1]

Sv Status

+ inService: Boolean [0..1]

Sv PowerFlow

+ p: ActivePower [0..1]

+ q: Reactive Power [0..1]

Sv TapStep

+ continuousPositio n: Float [0..1]

+ position: In teger [0..1]

IdentifiedObject

Core::Terminal

+ connected: Boolean [0..1]

+ sequenceNumber: Integer [0..1]

IdentifiedObject

Topology::

TopologicalNode

Equipment

Core::

ConductingEquipment

PowerSystemResource

Wires::TapChanger

0..*1

0..*

0. .1

0. .11

0. .1

1

0. .1

1

0. .11

0. .1

1

CIM: StateVariable CIM: Measurement • CIM: Command

Outline




• Testing Phase

• Conclusion

22

Testing Phases

• Software Testing Phase

– Simulation of data exchange within the SmartGen DMS

– Using DIgSilent simulator

• Cigré DER extended

• DMS Field Testing Phase

– SmartGen DMS in real networks

• Italian experimental areas

• Italian distribution network

23

SCADA Simulated Network

State Estimation

CIM 2 MAT

MAT 2 CIM

SCADA Real

Network

All DMS Functionalities

CIM 2 MAT

MAT 2 CIM

HV

0

12

1

TR_0_1

TR_0_2

13

14

2

3

4

5

11

S3

10

9

8

7

S2

6

S1

Feeder 1

Feeder 2

P,Q

V

I

Com 12

Res 12

Com 13

Com 14

Res 14

Res 8

P,Q Com 7

Res 6

Com 1

Res 1

V

I

P,Q

Res 3

P,Q

Com 3

Res 4

Res 11

H2 O

2 + -

Res 5

H2 O

2

+ -

P,Q Res 10

P,Q Com 10

H2 O

2

Res 9

Com 9

CH

P

Allocated measures

Measurements

PV 3 PV 4

PV 5

PV 9 PV 10

PV 6 PV 8

P,Q

P,Q

P,Q

P,Q

P,Q

P,Q P,Q

P,Q

P,Q

P,Q

P,Q

P,Q

P,Q

Diesel 9

FuelCell 9 FuelCell 10

FuelCell 5

Battery 5

Battery 10

P,Q

PV 11

Wind 7

Software Testing Phase – Simulated Network

SCADA Simulated Network

State Estimation

CIM 2 MAT

MAT 2 CIM

P,Q


CIM SV.xml MS.xm

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

25

Experimental Area ENEL I&R (Livorno)

Distribution netwotk AMAIE SpA (Sanremo)

Microgrid University of Genova

(Genoa)

LOAD

STORAGE

GENERATION

1 - Experimental Area in Livorno - ENEL

26

• Area owned by ENEL INGEGNERIA e RICERCA

• Internal network MV and LV:

– Common services and utilities(300kW)

– Pilot plants for combustion testing (1900kW):

– Experimental plants with distributed generation (1200 kW)

– Experimental storage systems (100 kW)

• Possibility of field tests with no impact on the distributor

• Functionalities that can be demonstrated


– Optimization

– Islanding

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 132/15 kV)

• double bar structure equipped with 2 transformers of 40 MVA.

– 10 MV feeders, typically managed in a radial structure, departing from the substation

– 115 km of MV lines, both cables and overhead lines. MV network managed in

compensated neutral

– ~ 200 secondary substations (MV/LV 15/0,4 kV), among public and private ones

• Of which about 10% remotely controlled

– ~30.000 users (27.000 for domestic use, 15 for industrial use, 3.000 other)

– ~50 PV plants

• 1 x 470 kW in MV

• 10 x (10-100kW) in LV

• Domestic < 6 kW

27


– Open/close control function

– Fault location


3 - VPP - University of Genoa

28

• Microgrid at a MV/LV substation

– Photovoltaic plant (20 kWp) • Monocrystalline module with 180 Wp.

• Expected production per year: 24,4 MWh

– Storage (10kW/12kWh) • Lithium battery technology

• Controllable loads

– System monitoring and real-time control

• Possibility of field tests with no impact on the distributor



– Optimization

– Islanding

PV Battery

Aux

Substation

Micro SCADA Substation

Outline




• Testing Phase

• Conclusion

29

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 CIM – Provides the SmartGen DMS with interoperability

– Allows the integration of CIM-based applications, with no additional implementation

– Enables to interface the SmartGen DMS with external CIM-based systems, without restricted access

• SmartGen contributes to – Diffusion of CIM as a commonly recognized standard for electrical data

representation

– Extension of CIM for the application to distribution network

30

Dr. Giulia Troglio Softeco Sismat S.r.l. [email protected]

www.smartgen.it

[email protected]

Dr. Federico Silvestro Università di Genova [email protected]

CIM for data exchange within a DMS

for electric distribution networks

HV

0

12

1

TR_0_1

TR_0_2

13

14

2

3

4

5

11

S3

10

9

8

7

S2

6

S1

Feeder 1

Feeder 2

P,Q

V

I

Com 12

Res 12

Com 13

Com 14

Res 14

Res 8

P,Q Com 7

Res 6

Com 1

Res 1

V

I

P,Q

Res 3

P,Q

Com 3

Res 4

Res 11

H2

O2

+ -

Res 5

H2

O2

+ -

P,Q Res 10

P,Q Com 10

H2

O2

Res 9

Com 9

CH

P

Allocated measures

Measurements

PV 3

PV 4

PV 5

PV 9 PV 10

PV 6 PV 8

P,Q

P,Q

P,Q

P,Q

P,Q

P,Q

P,Q

P,Q

P,Q

P,Q

P,Q

P,Q

P,Q

Diesel 9

FuelCell 9 FuelCell 10

FuelCell 5

Battery 5

Battery 10

P,Q

PV 11

Wind 7

Simulated Test Network

cim for data exchange within a dms for electric...

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