ideal grid for all Future flexible distribution system Seminar in Tampere 4 th of December 2015 Sami Repo (TUT) Ignasi Cairo (IREC) Zaid Al-Jassim (Dansk Energi) Davide Della Giustina (A2A) Alessio Dede (A2A) Luigi Vanfretti (KTH) Andrea Angioni (RWTH) Maite Hormigo (GNF) Mathias Christoffersen (Dansk Energi)
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Future flexible distribution system · 2015-12-04 · ideal grid for all SLIDE 2 04/12/2015 Agenda • 09.15 – 09.35 – IDE4L project and ANM concept / Sami • 09.35 – 09.55
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ideal grid for all
Future flexibledistribution systemSeminar in Tampere4th of December 2015
Sami Repo (TUT)Ignasi Cairo (IREC)
Zaid Al-Jassim (Dansk Energi)Davide Della Giustina (A2A)
impacts in Finland / Pertti Järventausta, TUT• 13.45 – 14.15 – Coffee & Poster session continues• 14.15 – 14.45 – Flexibility operator at Nordic demand response markets
/ Jan Segerstam, Empower IM• 14.45 – 15.00 – Conclusions• Visit to RTDS lab demonstration
WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
ideal grid for all 04/12/2015SLIDE 3
• IDE4L project overview and ANM concept
• Aggregator concept
• Developed functionalities
• Distributed automation system
• Demonstrations
• Conclusions
WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
ideal grid for all
From concept to demonstrations1. Defining the concepts
• Active network (D2.1)• Automation for active network management (D3.1)• Aggregator system (D6.1)
2. Developing planning methods and automationfunctionality
3. Building and running the demonstrations in:• Denmark (Østkraft Holding A/S)• Italy (A2A Reti Electtriche SpA)• Spain (Unión Fenosa Distribución, S.A.)
SLIDE 4 WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 201504/12/2015
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Expected outcomes (1/2)• Planning tools to design active distribution network
and to evaluate costs and benefits of developedconcept and technical solutions.
• Advanced automation system to extend monitoringand control functions deep in the distribution network.
• Increment of network hosting capacity for DG• Management of fast changing conditions and integration of
large number of DG and DR• Use of standards, like IEC 61850, for reusability and general
applicability to other EU scenarios• Aggregation of information from small-scale DERs and
flexibility services for distribution network management
04/12/2015SLIDE 5 WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
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Expected outcomes (2/2)• The same automation infrastructure to be utilized to
enhance the distribution network reliability• Automatic fault location, isolation and supply restoration
algorithm will be developed and demonstrated to improvethe reliability of distribution network.
• Design of a universal controller to enable flexible operationsof microgrids, smoothly transitioning from grid-supportingmode, grid-connected mode and islanded mode, whileguaranteeing quality of service.
04/12/2015SLIDE 6 WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
• Direct control• DSO’s own resources (OLTC, Reactive power compensation and FACTS)• Contracted non-market based control, e.g. voltage control of DG units• Emergency control to act just before protection
• Flexibility services from Commercial Aggregator• Scheduled re-profiling of flexible DERs• Conditional re-profiling of flexible DERs
SLIDE 13 WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 201504/12/2015
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Active network planning
• Active network becomes alternative for networkreinforcement
• Postponing investments of physical infrastructure by ANM• Replacing network reinforcement with smart functionalities
• Traditionally worst case design principle• Firm connection capacity always available for all customers• DG impactàmaximum production – minimum loading condition• Leads to over-dimensioning of network and the evaluation of smart
functionalities is limited to peak conditions• Stochastic planning of active network
04/12/2015SLIDE 14 WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
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0
50000
100000
150000
200000
250000
300000
350000
400000
Cosφ = 1.0 Cosφ = 0.92ind Vref = 1.02 CVC
Cost of losses + Use of grid fee - Distribution charge of DGLost revenue due to curtailment
DG lost income
DNO costs
Benefits of coordinated voltagecontrol in MV network
04/12/2015SLIDE 15
No control Primary control Secondary control
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Euro
s
ideal grid for all 04/12/2015SLIDE 16
• IDE4L project overview and ANM concept
• Aggregator concept
• Developed functionalities
• Distributed automation system
• Demonstrations
• Conclusions
WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
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FLEXIBILITYSERVICES
FLEXIBILITYSERVICES
PROSUMERS
Aggregation concept: keyenabler of “FLEXIBILITY”
FLEXIBILITYSERVICES
FLEXIBILITYSERVICES
04/12/2015SLIDE 17 WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
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State of the art - markets04/12/2015SLIDE 18
• The growing share of variablegeneration in Europe is increasingthe need for flexibility in theelectricity system.
• In this context, aggregation offersthe opportunity to exploit theflexibility potential of smallercustomers connected todistribution networks.
• Energy Efficiency Directive2012/27/EU – Legal basis fordevelopment
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State of the art - markets04/12/2015SLIDE 19
Some European demand response programs…
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State of the art - markets04/12/2015SLIDE 20
Some demand response providers…• Energy Pool (1,2GW capacity):
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Flexibility productsTwo types of standardized Flexibility Products
AD Product Conditionality ExampleScheduled re-profiling (SRP)
Unconditional(obligation)
The aggregator has the obligation toprovide flexibility services
Conditional re-profiling (CRP)
Conditional(real option)
The aggregator must have the capacityto provide flexibility services
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Aggregator: target markets• Three possible market uses for the
aggregator’s flexibility:
04/12/2015SLIDE 22
Procurement of balancing services (capacity) and activation ofbalancing energy by the TSO to balance demand and supplythrough the balancing energy market.
Network constraints resolution in all timescales, maintainingreliability and quality of service at TSO and DSO levels.Typical constraints refer to thermal ratings, voltageviolations, fault levels and transient stability issues.
Used by market players to meet their energyobligations in the market at minimum costs byarbitrating between generation and demandresponse on all different time horizons.
3. Portfolio optimization
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While ensuring furthercoordination between TSOs & DSOs
04/12/2015SLIDE 23
• Activation of flexibility resources connected to distributionnetworks by the TSO for the purpose of system balancing ortransmission constraints management may lead toconstraints in distribution networks
• Similarly, DSO constraint management will also affect theTSO grid and balancing of the system and the other way around
• Regarding energy markets, the program should be validated notonly for TSOs but also for DSOs.
• A robust and efficient IT framework is required to ensure thenecessary information exchange among commercialaggregators, DSOs, and TSOs.
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Aggregator concept• Within IDE4L project an aggregator concept is being
developed trying to ensure a robust, transparent andequitable market functioning.
• IDE4L aggregator concept consists of two new agents,evolving from their classical roles to include newfunctionalities
RetailerOffering a new service to customers
Commercial Aggregator
DSOInclude a set of new functionalitiesProcurement / Validation
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• IDE4L project overview and ANM concept
• Aggregator concept
• Developed functionalities
• Distributed automation system
• Demonstrations
• Conclusions
WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
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Congestion management
04/12/2015 WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015SLIDE 28
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IDE4L Solutions• Active network instead of a passive network
• Decentralized• Automated• Hierarchical
• Postponing the costly traditional solutions
• Using the full capacity of distribution networks• Monitoring the state of the network• Automatic decentralized solutions to solve congestions• Better use of distributed energy resources – e.g. through market place
Developed algorithms• State Estimation• Forecasting + State Forecasting• Secondary Power Control• Tertiary Control
04/12/2015SLIDE 29 WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
ideal grid for all 04/12/2015SLIDE 30
SE
PC
SF
DB
PF
LF
FC
SSAU
Aggregator
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DB: Data baseNRA: Network ReconfigurationMA: Market AgentFC: ForecasterSF: State ForecasterLF: Load ForecasterPF: Production ForecasterSSAU: Secondary Sub-station Automation unitPSAU: Primary Sub-station Automation unitDMS: Distributed Management SystemTC: Tertiary Controller
ideal grid for all 04/12/2015SLIDE 31
SSAU
Aggregator
SE
PC
SF
DB
PF
LF
FCPSAU
WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
DB: Data baseNRA: Network ReconfigurationMA: Market AgentFC: ForecasterSF: State ForecasterLF: Load ForecasterPF: Production ForecasterSSAU: Secondary Sub-station Automation unitPSAU: Primary Sub-station Automation unitDMS: Distributed Management SystemTC: Tertiary Controller
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SSAU
Aggregator
PSAU
DMS(TC)
NRA
MA
SF
DB
PF
LF
FC
Coordination
Market
DB: Data baseNRA: Network ReconfigurationMA: Market AgentFC: ForecasterSF: State ForecasterLF: Load ForecasterPF: Production ForecasterSSAU: Secondary Sub-station Automation unitPSAU: Primary Sub-station Automation unitDMS: Distributed Management SystemTC: Tertiary Controller
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NRAincluding PC
DT
SeveralPrimary
substations(MVPC)
Com. Aggregator Assets
ControlSignals
Market Agent
Com.Agg. 1
Com.Agg. 2
Com.Agg. 3
Com.Agg. 4
Com.Agg. k
Market Operator
SeveralSecondarysubstations
(LVPC) FLISR
Tertiary ControlTSOs
Biddingprocess
FlexibilityActivation
signal
Biddingprocess
OtherMarket
participants
CRP activation
ZAL21
ZAL22
ZAL23
Slide 33
ZAL21 I would rather call it a market place. A market operator will need a market to operate, thus another box would might be needed.Zaid Al-Jassim; 8.1.2015
ZAL22 1. The C- aggregator and T- aggregator will still need the external inputs such as weather data and so on. why its not included?
2. The T-aggregator will still need the DER schedule. Why its not included?Zaid Al-Jassim; 8.1.2015
ZAL23 I would rather call it DER because its only DER that we are controlling here. Flexibility is a little bit wider concept.Zaid Al-Jassim; 8.1.2015
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Real-Time Operation in the A2A Network: FLISR signal +high demand
• After a fault at F9 (highdemand) NRA restoresthe isolated loadappearing an overloadingin some branches of thenew topology.
• After a fault at the rest ofsections (F1…F14) NRArestores the isolatedwithout congestion.
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§ After Faults at F9 (high demand) NRA restores the isolated load, but line E23L01-SS545 remains congested in a 108% (new topology).
§ The market agent makes use of the available CRPs already contracted (shown inthe table).
Real-Time Operation in the A2A Network: high demand + fault at F9
NodeQuantity(↓ demand)
[kW]
Activation Price[€/MWh]
297 150 701006 150 701056 110 751512 150 70
§ Solution found:- Flexible loads at nodes 297 and
1006 should decrease in 150kW.
- Aggregated LV load at node1056 should decrease in 106kW.
- Cost of the activated flexibility:28.95 €/h (per activation).
Tertiary Control: Market Agent Algorithm
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Real-Time Operation in the A2A Network: FLISR signal +high demand
Tertiary Control Output
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-30000
-20000
-10000
0
10000
20000
Active Power in Congested Network
1a. BAU – Net Load 2b. Congestion – Net Load 2b. Congestion – Curtailed DG
Time [hours]
Activ
ePo
wer
[W]
Feeder capacity limit
The Low Voltage Power Controller is effectivein curtailing active from PV units…
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The LVPC is also effective at minimizingreactive power flows:
-3000
-2000
-1000
0
1000
2000
3000
4000
5000
Reactive Power Flow at Grid Connection
1a.BAU 1b.50%-DER 1c.100%-DER
Time [hours]
Rea
ctiv
ePo
wer
[VAR
]
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Dynamic Tariff (DT)• Dynamic tariff is changeable at different time and different
node, implemented by the following procedure:• Step 1: DSO collects information for day-ahead energy planning
• Step 2: DSO calculate and publish DT before closure of spot market
• Step 3: DR at the commercial aggregator side - Aggregator make energyplan based on DT and energy price
• Step 4: Commercial aggregator submit energy bids to spot market
Time frame of the DT method
04/12/2015SLIDE 39 WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
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Concept of DT Method forCongestion Management
Main features:• Decentralized control framework• The DSO has the chance to maximize the social welfare• It can be easily integrated into the existing market
3. Energy requirement
forecast
Information flowof the DT methodfor congestionmanagement
Info. with high reliabilityInfo. with low reliability
Power flow
04/12/2015SLIDE 40 WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
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How breakthroughs will be achieved
• Development of algorithms• Test of algorithms as individuals as well as one whole
system• Analysis of functionality and performance• Promoting economical values for DSO• Integration to the other pieces of the developed concept• Promoting an IDE4L concept
04/12/2015SLIDE 41 WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
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Feeder automation based onIEC61850
04/12/2015 WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015SLIDE 42
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Feeder Automation based onIEC61850• Design of a decentralized solution based on
the coordination among different IEDsdistributed along MV lines and the use ofIEC 61850 GOOSE communication servicesto accelerate the decision taken
04/12/2015SLIDE 43 WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
ideal grid for all 04/12/2015SLIDE 44
Background• 28% of the malfunctions of protection functions are
already caused by wrong configurations accordingto the North America Electric Reliability Corporationlast report
• Changes in topology for fault restoration andcongestion management
• Impact of high rate of DG connection on protectionsystems operation: Blinding effect, unnecesaryoperations, Failing autoreclosing, unintendedislanding…
WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
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Inflection point• Application of IEC 61850 standard for feeder
automation• Current trend of replacing switches by
breakers along distribution feeders• Frequent changes in network configurations to
fulfil optimization functions• Protection system reliable operations in
networks with DER and DG connection
04/12/2015SLIDE 45 WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
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IEC 61850 Protection FunctionParameters Update
• ObjectiveProcess to change remotely functional parameters and datasubscriptions in peer to peer communications withoutinterrupting operation
• Schema• Protection, monitoring and control functions modelled
with standardized Logical Nodes• Embedded Logic at IED level for dynamic reconfiguration• Use of MMS messages to update:
• LN setting values• GOOSE ID subscriptions
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Decentralized IEC 61850 FLISRSolution
Included Use Cases• FLISR using auto re-closers• FLISR based on distributed
control• Islanding protection using
communication command• Configuration of IEDs
Station
Control centerSCADA
IEC
6185
0IEC 61850-80-1
Guideline to exchange61850 information over IEC
60870-5-101/104
IEC 61850-90-1between stations
IEC 61850IEC 61850
IED IED CTs/VTs
RTULocal
SCADA
Power Utility substations AIEC 61850-7-4
IEC 61850-90-6MV network
Use of 61850for substation
tocontrol center
(expected)
Power Utility substation B
IEC 61850 parts, as of 2013XXX
XXX IEC 61850 future parts(already engaged) IEC 61850-90-15*: use of IEC 61850 over WAN can/will take advantage of
IEC 61850-80-1, IEC 61850-90-2 and IEC 61850-8-2 (web based) , and IEC 61850-90-12 (WAN)
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• ObjectiveDecentralized FLISR Schema based on IEC61850 GOOSEmessages that contemplates different interruption technologiesat distribution level, islanding mode protection and new IEC61850 guidelines
• Schema• Decentralized logic selectivity using GOOSE messages
• 1st Isolation Step – Performed by IEDs controlling circuit breakers.• 2nd Isolation Step – Performed by IEDs controlling switches.
• Loss of Mains Protection by means of IEC 61850 messagescontrolled by MV IEDs
• MMS messages to report status and interact with SAUalgorithms
Decentralized IEC 61850 FLISR SolutionWWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
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Decentralized IEC 61850 FLISRSolution
04/12/2015SLIDE 49
PSAUIED1
SS1
IED2 IED3
SS2
IED2 IED3
SS3
IED4 IED5
IED12
SS6
IED11 IED10
SS5
IED9 IED8
SS4
IED7 IED6
MGCC
Microgrid
Block Messages
MG
and
DG
Blo
ckC
losi
ng
MG and DG Block Opening
Breaker Status
FPI Block Messages
SW Status
IED5IED3IED1
Reclose Cycle Sucessfully Finished
IED7 IED6
FPI Block Messages
DG and MG Block Closing
DG and MG Unblock Closing
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Islanding ofmicrogrids
Distribution grid
Microgrid
Microgrid
DG
Background Microgrids may operateeither connected to thedistribution grid or as astandalone powersystem.
Interaction with thedistribution systemmust be taken intoaccount.
The breakthrough is theproposal of a protectiondevice that coordinateswith distribution gridbased on ICT
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Islanding of microgridsFeatures ofInterconnectionSwitch
Coordination with MV FLISR protection system.
The microgrid protection system uses IEC 61850.
Communication-Failsafe autonomous operation of the interconnection switch.
Automatic reclosing upon distribution grid restoration.
WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
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Breakthroughs Expected Results
• Reducing the number of customers affected bythe supply interruption
• Reducing restoration times
• Improve reliability and safety of protectionsystems
04/12/2015SLIDE 52 WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
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Optimal scheduling in futuresmart grids
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General CA concept and its interactionsWWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
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Day-ahead CA algorithm interactionWWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
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Real-time CA algorithm interactionWWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
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Commercial Aggregator functionalities
Prosumers portfolio
1 Consumption Forecasting
• Historical data• Weather forecast
Divides the consumersto groups with similarconsumption patterns
4 Market forecasting
• Base Load Profile• Modified Load Profile per request• Optimal Incentive Policy per request• Market price• Reliability of the clusters
2 Consumer Segmentation
Average consumer per cluster
3 Flexibility Forecast Tool
Simulates the behaviour of everyaverage consumer under differentprice and volume signals.
Obtains the aggregated response forthe whole clusters.
Forecast the marketprice of sold andpurchased electricity.
€
Methodologies rely on statistical andfinancial analyses of the markets.
Calculates the optimal incentiveand bidding policy in order tomaximize the profits of theCommercial Aggregator.
5 The CommercialOptimal Planning Tool
Participates in the markets
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CA Algorithms – some resultsScenario characteristics
Kind of area Urban
Number of nodes 40
Number of subestation 1
Area size
Penetration rate of Value
Domestic Users 100%
Solar Generation 20%
Wind Generation 5%
Electric Vehicles 15%
Flexible load profiles 70%
Cluster Startingtime
StoppingTime
PriceIncentives
Levels ofConsumption
2.1 10 21 0,17 1,2075
Example of applied Incentive Requests
WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
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Interfacing TSOs and DSOs viaPMU-based information exchange
04/12/2015 WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015SLIDE 59
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Data Flow
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IEC 61850-90-5 Gateway
for
IEEE C37.118.2 Synchrophasor DataTransfer
SLIDE 61 WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 201504/12/2015
• Theory:• IEEE C37.118 à Synchrophasor data transfer by exchange of 4 types of messages:
1. Data, 2. Configuration, 3. Header and 4. Command Frames
• IEC 61850-90-5 à PMU data (Based on C37.118) mapped to IEC 61850 Data Modelà Communication mechanism: Routed-Sampled Value and Routed-GOOSEàMulticast UDP/IP
(1) IEEE C37.118 PMU Dataà (2) IEC 61850 Data Model & Datasetà (3) IEC 61850 Routed-Sampled Value / GOOSE Publisher and (4) Subscriber
LPHD.PhyHealth.q
LPHD.PhyHealth.t
MMXU1.Health.q
MMXU1.Health.t
LPHD .PhyHealth.StVal
MMXU1.Hz.q
MMXU1.Hz.t
MMXU1.HzRte.ma g.fMMXU1.HzRte.q
MMXU1.HzRte.t
MMXU1.Health.StVal
MMXU1.A. PhsB.t
MMXU1.A.PhsC.cVal .mag.fMMXU1.A.PhsC.cVal .ang.f
MMXU1.A.PhsC.q
MMXU1.A.PhsC.t
MMXU1.Hz.mag.f
MMXU1.A.PhsB .cVal .mag.fMMXU1.A.PhsB.cVal .ang.f
MMXU1.A. PhsB.q
MMXU1.PhV. PhsB.t
MMXU1.PhV.PhsA.cVa l .ang.fMMXU1.PhV.PhsA.q
MMXU1.PhV.PhsA.t
MMXU1.PhV.PhsB.cVa l .mag.fMMXU1.PhV.PhsB.cVa l .ang.f
MMXU1.PhV. PhsB.q
MMXU1.PhV.PhsA.cVa l .mag.f
DataSetSynchrophasor Data
IEC 61850-90-5 frame specification
Connection with PMUBased on
IEEE Std C37.118
UDP/IP
WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 201504/12/2015
• Implementation and Results• HIL Real-time simulationà SmarTS Lab
• Conformance of the functionality of the library with the requirements of IEEE C37.118.2 and IEC61850-90-5 is validated.
WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 201504/12/2015
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Applications
Providing Dynamic Information
SLIDE 64 WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 201504/12/2015
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Dynamic Model Synthesis ofDistribution System
Data curation, fusionand extraction of
steady state component• Ambient Data Analysis
(for stochasticvariations)
• Ringdown Data Analysis(for transients)
TSO
Calculation ofstability indices
Data processand analysis
Data processand analysis
Data processand analysis
CentralizedArchitectureDecentralizedArchitecture
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Centralized vs decentralizedarchitecture (better observability)
Dynamic Stability Indices
Decentralized Mode Estimation
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Centralized vs decentralizedarchitecture (local mode visibility)
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Voltage Stability Analysis in Distribution NetworksSLIDE 68
68
By samplings from PMU1 and PMU2,three different equivalent models aredeveloped
Computation of stability indicators based on real-time measurements and equivalent models.
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69
Three different PV curves are calculated from the three models.The voltage stability and instability indices are calculated from these models to indicate thecontributions of two networks on the voltage stability.
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SLIDE 70
LABVIEW Application
Real-time simulations results for aggregatedload (LV network) seen from PMU22:
A. all distributed generations inside MV networkare disconnected
B. all distributed generations inside MV networkare connected
A B
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• IDE4L project overview and ANM concept
• Aggregator concept
• Developed functionalities
• Distributed automation system
• Demonstrations
• Conclusions
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1. Use Cases
2. SGAMArchitecture
3. Implementationof architecture
4. Field and LabDemonstration
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1. Use Cases
MonitoringUse Cases
Control UseCases
BusinessUse Cases
• State estimation, forecast, network update, measurement collection• LV, MV, control center power control, block OLTCs, FLISR• Purchase of energy and flexibility, activation of flexibility
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1. Use CasesUse Case description
Steps Information producer Information receiver Function Information exchanged Requirement
Each component has been defined in terms of• Interfaces• Database• Functions
New actor developed :• Substation Automation UnitFurther development for• Commercial aggregator• Distribution management system (DMS)• MicroGrid Central Controller
Alsopresent infunction
layerand UCs
WWW.IDE4L.EU – Tampere Dissemination Activity 4th December 2015
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2. SGAM architectureInformation layer
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Network static data
IEC 61850 – data modelsLogical node Data object Data Attribute
ATCC BndCtr ASG setMag AnalogueValue
CIM – data models
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2. SGAM architectureCommunication layer
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Steps Informationproducer
Informationreceiver
Function Informationexchanged
Requirement
1 SAU(PSAU).MMS SAU(SSAU).MMS DataReport
Switch Status Transfer Time = 500 msTransfer Rate = 1000 kb/sSynchronization accuracy = …Availability = …
2 … … … …
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Function layer• Functions have been realized in WP4 (FLISR), WP5
(Monitoring and LV, MV, control center control),WP6 (business and commerical aggregator)
• Functions are adapted in order to read and writefrom a standardized IDE4L database
and data attribute• set of information to parameterize the communications
interface to each physical device (such as IP addresses,TCP ports, users and passwords, etc.)
Management Model• Represents the models related to an
algorithm.• instantiate, parameterize and control the
execution of a specific algorithm
Bridge ModelIt is the connection schema forall other schemas. In this datamodel every relation amongMeasure & Control, Managementand Network are described
Network ModelContains the network topology and parameterrepresentation
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4. Field and Lab demonstrationUse Case mapping, KPIs
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Use Case mapping and KPIs• All use cases have been assigned to demonstrators• Each use case has a set of Key Performance Indexes (KPIs) in order to evaluate
the performance of the architecture (deliverable 7.1)Field demonstrators• Real loading/generation conditions
• real PQ issues• real congestions
• Real amount of information exchanged• Real componentsLab demonstrators• “Real”à “Realistic” (past data or collection of statistics)• Tests with different time windows and simulation stepsà check different
issues of PQ, congestions• It is possible to introduce errors/issues in different parts of monitoring/control
chain
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Conclusions and Exploitation of IDE4Larchitecture
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1. Use cases• Around 30 use case detailed descriptions• List/description of actors, information exchange, functions and requirements(D3.1 and D3.2)
2. SGAM architecture• SGAM communication, information, component, business layer in .xls or
enterprise architect files(D3.2)
3. Architecture Implementation• 61850, CIM information mapping .xls tables to facilitate standard
implementation of architecture• Database structure and sample communication interfaces(D3.2)
4. Field and Lab demonstration• Demonstration results(D7.2)
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• IDE4L project overview and ANM concept
• Aggregator concept
• Developed functionalities
• Distributed automation system
• Demonstrations
• Conclusions
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Lab Demo Site
Field Demo Site
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Lab Demo Site
Field Demo Site
Copenhagen, Denmark
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Lab Demo Site
Field Demo SiteBrescia, Italy
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Building-blocks, e.g.:1. Algorithms2. TLV’ devices3. Third party devices4. Third party software
Groups of building-blocks, e.g.:1. State estimation
algorithm within a PCconnected to an RTUvia a 61850 interface
Use cases, e.g.:1. Monitoring of LV grid
(PC + state estimation+ RTU + Smart meters +interfaces)
Integration lab.The testing approach: a three-steps procedure
1stDev. lab 2nd
Integration. lab 3rdDemo
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A2A
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