ideal grid for all
Distributed and hierarchical congestion management in distribution networks containing distributed energy resources
Tutorial in ISGT Europe 2016 conference
Ljubljana, Slovenia
Sunday October 9th 13:30-15:00
Professor Sami Repo, Tampere University of Technology
Senior Scientist Anna Kulmala, VTT Technical Research Centre of Finland
IDE4L is a project co-funded by the European
Commission (Project no: 608860)
ideal grid for all 10/04/2017SLIDE 2
• Active Network Management concept
• Distributed automation system
• Congestion management concept
• Demonstrations
• Conclusions
WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
ideal grid for all
The Project at a glance
• FP7 demonstration project (9/2013 – 10/2016)
• Scope: Active distribution network management• From the planning to the real-time operation
• From the MV up to LV single customer
• DSO interaction with TSO, DER, μGrid and Aggregator
SLIDE 3 10/04/2017 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
ideal grid for all
Breakthroughs
18/05/2016SLIDE 4
WP2Planning tools for distribution
network management
ANM concept
Target and expansion
planning including ANM
Operational planning including DER uncertainty
WP3 Distribution
network automation architecture
Automation concept
Smart meter as a sensor
Testing Platform for monitoring & control systems
Hierarchical and decentralized automation
WP4 Fault location, isolation and
supply restoration
Decentralized FLISR
IEC 61850 Distribution
Protection System Reconfiguration
Microgridinterconnection
switch
WP5Congestion
management
Decentralized state estimation and state forecast
Tertiary control –Network
reconfiguration
Secondary control – Coordination of voltage controllers
Dynamic tariff
WP6Distribution
networks dynamics
Aggregator concept
Optimal scheduling of flexibility
Transmitting synchro-phasors &
real-time model syntheses
Improved microgridoperation
WP7 Demonstrations
WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
Concept Monitoring Control Market
ideal grid for all
MicrogridsEnergy communities
Vision of future smart grid
System management and design
Advanced monitoring
Market design
Aggregator
Smart charging of EV Smart homes and PV
Storage
Controllable loads and energy efficiency
Power to gas
BalancingDistribution automation
Renewable energy resources
Grid infrastructure
ideal grid for all
Policies of electricity network
• Today networks are always over-dimensioned due to quality of supply obligations and missing possibility to control DERs
• Some companies are already forced to utilize production curtailment to manage their networks
• In future more flexibility is needed to integrate more RES and DERs in power system
• Controllability of distribution network via advanced ICT
• Decentralization of network management due to scale of the system
SLIDE 6 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 201618/05/2016
ideal grid for all
Active distribution network• Active distribution network utilize DERs in grid management Active Network Management (ANM)
• DERs are integrated as part of grid and markets instead of ”fit and forget” connection
• ANM should provide synergy benefits for DSO and customers
18/05/2016 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016SLIDE 7
ideal grid for all
IDE4L automation architecture
18/05/2016SLIDE 8 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
Commercial
aggregator
systems
DSO
Energy retailer
Market
operator
platform
Balance
responsible party
TSOAMR HUB
Control HUB
Weather HUB
DG
IED
DR
Weather
data
Enterprise Service Bus
DMSMDMS CISNIS
SCADA NIS
Substation automation
Secondary substation
automation
IED
IEDRTU
Secondary substation
automation
IED
PMU
PMU PQ
Smart
meters
Smart
meters
DER automation RTUDER automation
Commercial aggregator
IED
DG
IED
DR
IED
ideal grid for all
Roles of grid operatorsand aggregator
1. DSO/TSO• Validates the submitted offers:
• Off-line validation
• Real-Time validation
• Purchases flexibility services for avoiding network constraints
• Calculates and provides the Flexibility Table (Limits for each Load Area)
2. Aggregator• Forecasting of consumption, production, price, etc.
• Flexibility estimation of customers
Determination of market bids
• Commercial optimal planning
Maximization of aggregator profit
18/05/2016SLIDE 9 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
ideal grid for all
Monitoring, protection and control system• Complete network will be monitored and controlled
• Intelligent Electronic Devices (IEDs)
• Coordination and merging of information and decisions at substations
• DA applies variety of communication technologies• Primary substations - SCADA and possibly other IT systems (fibre optics,
wireless)
• Secondary substations and MV switching stations (wireless)
• Smart meters (PLC or wireless)
• Ethernet is becoming the prevalent communication standard for all automation devices
• IEC 61850 GOOSE and MMS
• DLMS/COSEM
• IEC 60870-5-104
• Modbus/TCP over LAN/WAN
SLIDE 10 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 201618/05/2016
ideal grid for all
Control of DERs from DSO’s viewpoint• Regulation
• Connection requirements technical capabilities for the control of DERs
• Dynamic tariffs to incentivize load shifting• Retail off-peak day-ahead prices
• Grid off-peak network load
• 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 11 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 201618/05/2016
ideal grid for all
Active network planning
• Active network becomes alternative for network reinforcement
• 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 impact maximum 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• Non-firm connection (based on dedicated contract) increase network
hosting capacity remarkably
• Enable full utilization of ANM
18/05/2016SLIDE 12 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 13
• Active Network Management concept
• Distributed automation system
• Congestion management concept
• Demonstrations
• Conclusions
ideal grid for all
General architecture
10/04/2017 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016vSLIDE 14
ideal grid for all
Motivation
SLIDE 15
• Background• Little monitoring penetration in the
distribution grid:• primary substations
• secondary substation remote control
• average values only
• Electronic meters deployment mainly for billing and CRM
• Needs to be developed• LV grid: EV, PV, HP and demand-response
schemes mainly affect the LV grid
• Secondary susbtations: Improve the monitoring, protection and control of secondary substations
• TSO-DSO: Need of dynamic information from DSO grid
10/04/2017 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
ideal grid for all
Pillars
SLIDE 16
• Amount of data increases • 10 of PSs -> 106 customers
• averages only -> high-frequency measurements
• Decentralized approach• Data is collected/processed locally (LV
data -> in SS; MV data -> in PS)
• Only summary/alarms are reported to upper levels
• Benefit: impact on CAPEX (scalability / modularity)
• Less-demanding communication is required
• Faster response
• reuse of existing automation components
10/04/2017 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
ideal grid for all
Pillars
SLIDE 17
• The number/type of monitoring devices are increasing
• Smart meters
• Fault detectors / protections
• Power quality meters / PMU
• Standards are needed to:• Limit the integration time
• Limit the maintenance time
• Main standards:• CIM for grid assets
• 61850 for data about the grid
• DLMS/COSEM for metering data
• Benefit: Positive impact on CAPEX and OPEX (interoperability)
10/04/2017 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
ideal grid for all
Commercial aggregator market setup
10/04/2017 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016SLIDE 18
Purchase/Sale bids
Commercial Aggregators
Wholesale Market
Other market
participants
Bilateral contracts
Flexibility market
Sale bids
TSO
Flexibility activation requests
Flexibility procurement
DSOs
Flexibility procurement
Flexibility activation requests
Flexibility validation
Consumers Prosumers
Flexibility activation requests
TSO
/DSO
co
ord
inat
ion
Market clearing
Market clearing
Market clearing
Market clearing
PurchaseSale bids
ideal grid for all
Market operator (MO) as neutral market facilitator
10/04/2017 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016SLIDE 19
ideal grid for all 18/05/2016SLIDE 20
Flexibility productsTwo types of standardized Flexibility Products
AD Product Conditionality Example
Scheduled re-
profiling (SRP)
Unconditional
(obligation)
The aggregator has the obligation to
provide flexibility services
Conditional re-
profiling (CRP)
Conditional
(real option)
The aggregator must have the capacity
to provide flexibility services
WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
ideal grid for all
Aggregator’s real time algorithm
18/05/2016SLIDE 21 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
DSO
Aggregator
DERs
1
2 3 7
5
2 64 8
• 1: Order of flexibility activation
• 2: Status request (baseline + available flexibility) and operational status return
• 3: Allocation of flexibility volume among DERs proportional to their available amounts
• 4: DERs’ activation
• 5: Activation confirmation
• 6: Energy measurements (request and return)
• 7: Modification of flexibility volume target for remaining activation period and re-allocation of set points among DERs
• 8: Sending of modified control set points
ideal grid for all
Comparison of architectures
Distributed / Decentralized
• Local challenges
• Small-scale resources
• Scales well to whole system
• Less dependent on communication
• Needs to be coordinated with centralized systems
• Supports novel ideas: active networks and microgrids
• Information exchange is the key question for successful implementations
Centralized
• Global challenges
• Large-scale resources
• Scalability is an issue
• Very dependent on communication
• Does not necessarily require existence of distributed ach.
• Less flexible for novelties
• Software integration and communication QoS are the key questions
10/04/2017 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016SLIDE 22
ideal grid for all
Substation Automation Unit (SAU)
10/04/2017 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016SLIDE 23
ideal grid for all
Use cases
SLIDE 24
IDE4L hierarchical network management
… a (very) simplified description …
1. Monitoring• Real-time monitoring
• Load and production forecasting
• State estimation and forecasting
• Dynamics of distribution grid
2. Protection• Logic selectivity
• FLISR with DERs and μGrid
3. Control• Congestion management
• Optimal scheduling
• μGrid voltage control
• Dynamic grid tariff
Monitoring
CB, OLTC
Short-term forecast
State estimation
Secondary control
IED, Primary control
CB, DER
IED, Primary control
Tertiary control
Long-term forecast
Day-ahead market
Real-time/intra-hour
Day-ahead and Intra-day
Hard real-time
e.g. fault location
e.g. V/VAr regulation
e.g network reconfiguration
Secondary control
Flexibility market
Commercial aggregator
e.g. DER scheduling
e.g. CRP and SRP signals
Market
Tertiary controller
Secondary controller
Monitoring Estimation
Forecasting
Primary controller
Primary device
10/04/2017 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
ideal grid for all
Substation Automation Unit
10/04/2017 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016SLIDE 25
SAU
Interfaces
Database
Applications
DLMS/COSEM
MMS
Prosumers – Smart meters and DER IEDs
Control Center - DMS
Substations - IEDs
IEC 61850
CIMManagement
model
Bridge model
State Estimation
Power control
ForecastData Acquisition
Reports
ideal grid for all
DemonstrationsSLIDE 26
Testing phase: a three-step procedure
Building-blocks, e.g.:
1. Algorithms2. Protection devices3. Third party devices4. Third party software
Groups of building-blocks, e.g.:
1. State estimation algorithm within a PC connected to an RTU via a 61850 interface
Use cases, e.g.:
1. Monitoring of LV grid (PC + state estimation + RTU + Smart meters + interfaces)
1stDev. lab 2nd
Integration. lab 3rdDemo
10/04/2017 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
ideal grid for all
Unareti Demo Site Overall Architecture
18/05/2016 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016SLIDE 27
BRESCIACONTROL CENTER
PRIMARY SUBSTATION AUTOMATION UNIT
PROTECION SYSTEMS
PRIMARY SUBSATION SCADA SYSTEMS
SMART METER
PRIMARY SUBSTATION
LEVEL
SECONDARY SUBSTATION
LEVEL
LOW VOLTAGE NETWORK LEVEL
PHOTOVOLTAIC PANEL
STORAGE
MV Demonstrator
LV Demonstrator
SECONDARY SUBSTATION AUTOMATION UNIT
PROTECTION SYSTEMS
BREAKERS
ideal grid for all
LV Network Demonstrator
18/05/2016 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016SLIDE 28
ideal grid for all
Net load forecast of prosumers
10/04/2017 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016SLIDE 29
Ostkraft Fenosa, producer
Unareti
ideal grid for all
State estimation
10/04/2017 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016SLIDE 30
Ostkraft
Unareti
ideal grid for all
Design and implementation of SAU
10/04/2017 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016SLIDE 31
ideal grid for all 18/05/2016SLIDE 32 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
1. Use Cases
2. SGAM Architecture
3. Implementation of architecture
4. Architectureevaluation
ideal grid for all 18/05/2016SLIDE 33
1. Use Cases
MonitoringUse Cases
Control Use Cases
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
WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
ideal grid for all 18/05/2016SLIDE 34
1. Use CasesUse Case description - example
Steps Information producer Information receiver Function Information exchanged Requirement
1
2 … … … …
Information exchanged
Switch statusVoltage measuremenCurrent measurementPower/energy
measurement
Functions
Data acquisition
Data report
Data storage
Signals sampling
Statistical calculation
ActorsSAU(PSAU).MMSSAU(PSAU).RDBMSSAU(PSAU).IEC104DMS.MMSSensorSAU(SSAU).MMSDMS.ModbusSAU(PSAU).FunctionsSAU(PSAU).ModbusDMS.IEC104IED(PSIED).MMS
IED(PSIED).functions
Requirements
Requirement: transfer time
Requirement: Transfer rate
Requirement:
Synchronization
Requirement: Availability
SAU(PSAU).MMS SAU(SSAU).MMS Data Report Switch Status TT = 100 ms …
WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
ideal grid for all
2. SGAM architectureGeneral description and link to use cases
18/05/2016SLIDE 35
1. Business framework
2. Functions to be implemented
3. Data models in the main automation standards
4. Communication protocols
5. Components, both hardware and software to take part to the automation system
Smart Grid Coordination Group, CEN-
CENELEC-ETSI, Tech. Rep., 2012
WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
ideal grid for all
2. SGAM architectureBusiness layer and mapping to component layer
18/05/2016SLIDE 36
Business layer
• Business actors are connected by business transaction
• Each one has a business goal
• Business actors are mapped onto components
Business goals
Transmission System Operator
(TSO)
Service Provider (SP)
Market Operator (MO)
Commercial aggregator (CA)
Distribution System Operator (DSO)
Retailer
Prosumer
Power schedule and activation price
Business transactions
WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
DSO
Prosumer
Transmission System Operator (TSO)
Service Provider (SP)
Market Operator (MO)
Commercial aggregator (CA)
TSO Energy management system
Service provider platform
Market Operator platform
Commercial aggregator system (CAS)
Intelligent Electronic Device (IED)
Substation Automation Unit (SAU)
MicroGrid Central Controller (MGCC)
Distribution Management System (DMS)
„Business Actors“ „Automation Actors“
Ensure market settlement
Maximize income from energy selling
and purchase
Monitor of grid status, power quality and
sequrity requirements
Sell services as price, weather, generation
forecasts
Optimize energy costs of portfolio
ideal grid for all
2. SGAM architectureComponent layer
18/05/2016SLIDE 37
Sensor Actuator
Transmission System Operator Energy Management System
(TSOEMS)
Service Provider Platform (SPP)
Market Operator Platform (MOP)
Commercial aggregator automation system (CAAS)
Intelligent Electronic Device (IED)
Substation Automation Unit (SAU)
MicroGrid Central Controller (MGCC)
Distribution Management System (DMS)
0..*
1..*1..*1..*
1..*
0..* 0..*
1..*
1..*
1..*
0..*
0..*
1..*
1..*0..*
Substation automation unit (SAU)
MMS
Relational database managment system (RDBMS)
Time series database (TSDB)
Interfaces
Database
Functions
SAU
Modbus
· Data report· Data storage· Check flag· CIM parsing· Data reconstruction· Detect error· Fault isolation· Load forecast· Missing data· Optimal power flow· power quality control· power quality indexes· algorithm performance index· Second fault isolation· State estimation· State forecast· Statistical calculation· Data acquisition· Protection update· Reading/Writing IEDs setting
DLMS/COSEM
IEC 61850-90-5
Web Services (WS)
Each Automation actor is defined in terms of
• Interfaces
• Database
• Functions
New automation actors developed :
• Substation Automation Unit
Further development for
• Commercial aggregator
• Distribution management system (DMS)
• MicroGrid Central Controller
Also present in function
layerand UCs
WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
ideal grid for all
Bid acceptance/modification
Bid submission
Check flag
CIM parsing
Commercial optimal planning
CRP activation request
CRP Validation request
Data acquisition
Data Curation and Fusion
Data reconstruction
Data report
Data storage
Detect error
Dynamic info derivation
Fault detection
Fault isolation
Load area configuration
Load forecast
Market clearance
Market infos
Missing data
Non-convergence detection
open/close switch
Optimal power flow
power flow
power quality control
power quality indexes
Protection update
algorithm performance index
Reading/Writing IEDs setting
Second fault isolation
Signals sampling
State estimation
State forecast
Statistical calculation
synchronization
Validation reply
Validation request
2. SGAM architectureFunction layer
18/05/2016SLIDE 38
Functions are mapped to
• Actors
• Use cases
• Zones and domains of Smart Grid Plane
LV real time Monitoring
WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
SAU
Function list
MV real time Monitoring
MV State Estimation
Control Center Power Control
MV Power Control
DMS
MGCC
IED
ideal grid for all
2. SGAM architectureInformation layer
18/05/2016SLIDE 39
class Business Context View -PSAU-SSAU
Components::PSAU
Computer
Components::SSAU
Computer«Information Object» Network static data
«Information Object Flow»
«Information Object» OLTC control
«Information Object Flow»
«Information Object» State Estimate/forecast
«Information Object Flow»
«Information Object» State Estimate/forecast
«Information Object Flow»
«Information Object» Current/Voltage Meas., «Information Object» Meas. statistics,
«Information Object» Power/Energy Meas., «Information Object» switch status
«Information Object Flow»
IEC 61850 – data models Logical node Data object Data Attribute
ATCC BndCtr ASG setMag AnalogueValueCIM – data models
WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
class Business Context View -SSAU-IED
Components::D
:IED
Components::SSAU
Computer
Components::
SS :IED
Components::MGCC
Computer
Components:
:D :PMU
Components:
:DIED :
Interconnection
Switch
Components:
:DIED :
Smart
meter
Components:
:DIED :
SW-CTRL
Components:
:SSIED:
MDC
Components:
:SSIED :
SW-CTRL
Components:
:SSIED :
AVC-CTRL
Components:
:SSIED :
PMU
Components:
:PS :PMU
Components:
:SSIED :
RTU
«Information Object» Setting values of IEDs
«Information Object Flow»
«Information Object» Setting values of IEDs
«Information Object Flow»
«Information Object» Current/Voltage Meas.,
«Information Object» Frequency Meas.
«Information Object Flow»
«Information Object» Current/Voltage Meas.,
«Information Object» Frequency Meas.
«Information Object Flow»
«Information Object» Current/Voltage Meas.,
«Information Object» Power/Energy Meas.,
«Information Object» switch status
«Information Object Flow»
«Information Object» Current/Voltage Meas.,
«Information Object» Power/Energy Meas.,
«Information Object» switch status
«Information Object Flow»
«Information Object» Current/Voltage Meas.,
«Information Object» Power/Energy Meas.,
«Information Object» switch status
«Information Object Flow»
«Information Object» flags
«Information Object Flow»
«Information Object» status polling
«Information Object Flow»
class Canonical Data Model
Generation Transformation Distribution DER Customer Premise
Market
Enterprise
Operation
Station
Field
Process
Name: Canonical Data Model
Author: chn
Version: 0.3
Created: 17.6.2013 14:14:17
Updated: 1.7.2015 9:50:42
Canonical
Data
Model
«Data Model Standard»
CIM/XML
«Data Model Standard»
IEC 61850-7-4/ IEC 61850-7-420
«Data Model Standard»
DLMS/COSEM
ideal grid for all
2. SGAM architectureCommunication layer
18/05/2016SLIDE 40
Transmission System Operator Energy Management System
(TSOEMS)
Service Provider Platform (SPP)
Market Operator Platform (MOP)
Commercial aggregator automation system (CAAS)
Intelligent Electronic Device (IED)
Substation Automation Unit (SAU)
MicroGrid Central Controller (MGCC)
Distribution Management System (DMS)
Tech 11 Tech 11
Tech 11
Tech 11
Tech 11
Tech 11 Tech 1
Tech 10
Tech 11Tech 1
Tech 1Tech 1Tech 1
Tech 1
Tech 1
Tech 11
Steps Information
producer
Information
receiver
Function Information
exchangedRequirement
1 SAU(PSAU).MMS
SAU(SSAU).MMS
Data Report
Switch Status Transfer Time = 500 msTransfer Rate = 1000 kb/sSynchronization accuracy = … Availability = …
2 … … … …
WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
ideal grid for all 18/05/2016SLIDE 41
Function layer
• Functions have been realized in WP4 (FLISR), WP5 (Monitoring and LV, MV, control center control), WP6 (business and commercial aggregator)
• Functions are adapted in order to read and write from a standardized IDE4L database
Smart Grid Coordination Group, CEN-
CENELEC-ETSI, Tech. Rep., 2012
Communication layer
• The requirements of the information exchange grouped onto technology classes
2. SGAM architectureOne step toward implementation
Information layer
Exchanged data are clustered onto classes and mapped to
• CIM data models for static data and business related data
• 61850 for real time data
Component layer
Each component is implemented as
• Software/Hardware interfaces
• Database
• Functions
WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
ideal grid for all
3. Implementation of architectureDatabase structure
18/05/2016SLIDE 42
Measure & Command Model
• Physical devices, logical devices, logical nodes, data objects and data attributes with real time data
• Set of information to parameterize the communications interface to each physical device (such as IP addresses, TCP ports, users and passwords, etc.)
Measure&CommandModel
NetworkModel
BridgeModel
ManagementModel
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 for all other schemas. • Relations among Measure & Control
real time quantities with the network topology
Network Model• Network topology and parameters of lines,
customers and generators
WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
ideal grid for all
Conclusions and Exploitation of IDE4L architecture
18/05/2016SLIDE 43
1. Use cases
• 29 use case detailed descriptions (11 monitoring, 11 control, 7 business)
• List with description of actors, information exchange, functions and communication requirements
2. SGAM architecture
• SGAM communication, information, component, business detailed SGAM layers in .xls and enterprise architect files
3. Architecture Implementation
• 61850, CIM information mapping for whole set of information exchanges in UCs in .xls tables to facilitate standard implementation of architecture
• Database structure and sample communication interfaces
4. Evaluation of architectures
• Architecture metrics definition and results
WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 44
• Active Network Management concept
• Distributed automation system
• Congestion management concept
• Demonstrations
• Conclusions
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 45
HV/MV MV/LVMV feeder LV feeder
Voltage
1 pu
Permissible
voltage
variation
Allowable
range of
substation
voltage
Minimum load, substation voltage at its highest value
Maximum load, substation voltage at its lowest value
Transformer
tapping boost
Transformer
voltage drop
LV feeder
voltage drop
MV feeder
voltage drop
Voltage drop margin
Voltage rise
margin
Voltage profiles without generation
Why congestion management?
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 46
Why congestion management?
HV/MV MV/LVMV feeder LV feeder
Voltage
1 pu
Permissible
voltage
variation
Allowable
range of
substation
voltage
Minimum load, substation voltage at its highest value
Maximum load, substation voltage at its lowest value
Transformer
tapping boost
Transformer
voltage drop
LV feeder
voltage drop
MV feeder
voltage drop
Voltage drop margin
Voltage rise
margin
HV/MV MV/LVMV feeder LV feeder
Voltage
1 pu
Permissible
voltage
variation
AVC relay
dead band
(2 DB in
Figure 3.2)
Minimum load, maximum generation, substation voltage at its highest value
Maximum load, no generation, substation voltage at its lowest value
Maximum load, maximum generation, substation voltage at its lowest value
Voltage outside the permissible range
Voltage profiles
with generation
Allowable
range of
substation
voltage
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 47
Why congestion management?
HV/MV MV/LVMV feeder LV feeder
Voltage
1 pu
Permissible
voltage
variation
Allowable
range of
substation
voltage
Minimum load, substation voltage at its highest value
Maximum load, substation voltage at its lowest value
Transformer
tapping boost
Transformer
voltage drop
LV feeder
voltage drop
MV feeder
voltage drop
Voltage drop margin
Voltage rise
margin
HV/MV MV/LVMV feeder LV feeder
Voltage
1 pu
Permissible
voltage
variation
AVC relay
dead band
(2 DB in
Figure 3.2)
Minimum load, maximum generation, substation voltage at its highest value
Maximum load, no generation, substation voltage at its lowest value
Maximum load, maximum generation, substation voltage at its lowest value
Voltage outside the permissible range
Voltage profiles
with generation
Allowable
range of
substation
voltage
Active congestion
management methods
decrease the total costs
of the network in many
cases
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 48
Control hierarchy of congestion management
• Secondary control manages resources in one MV or LV network
• Mitigates congestions and optimizes the network state
• Operates through changing the set points of primary controllers
• Based on state estimation results
• Tertiary control utilizes forecasts for a longer time interval and manages the whole distribution network
• Network reconfiguration
• Real power control through the market place
• Dynamic tariff
Real and reactive
power controllers
AVC relay
SSAU
SSAU
MV/LV
HV/MV
Load
controller
ACDC PV
Converter
controller
MV/LV
... LV
Compensator
controller
Tertiary control
Set points
Database
Load and
production
forecast
State
estimation
Secondary
power control
Interfaces to primary controllers, measurement
devices, SSAUs and control centre
...Algorithms
Smart meter
Measurement data
PSAU
Control centre
Switch
controller
DMS/SCADA Market place
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 49
Interactions of the congestion management system
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 50
• Load and production forecast, state estimation and real time power control algorithms are functions of the SAU and are responsible for monitoring and control of either one MV or one LV network
• All information exchange between the functions is realized through the database
• Monitoring and load and production forecast functions are executed asynchronously
• State estimation and power control execution is synchronized by using database flags
Real time monitoring and secondary control
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 51
• The load and production forecast algorithms are time series forecasteralgorithms
• The state estimation algorithm is a weighted least squares state estimator that uses branch currents as state variables
• The power control algorithm is an optimal power flow (OPF) algorithm implemented using sequential quadratic programming (SQP) algorithm
• The objective function is formulated to minimize network losses, production curtailment, load control actions, the number of tap changer operations and the voltage variation at each node.
Real time monitoring and secondary control
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 52
Network reconfiguration and market agent algorithms
• The network reconfiguration and the market agent algorithms are executed sequentially
• Both are optimizing algorithms: network reconfiguration utilizes genetic algorithm and the market agent primal/dual interior point algorithm
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 53
• Active Network Management concept
• Distributed automation system
• Congestion management concept
• Demonstrations
• Conclusions
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 54
Lab Demo Site
Field Demo Site
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 55
Lab Demo Site
Field Demo Site
Secondary controldemonstrations
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 56
Demonstrated in laboratories and real distribution networks
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 57
Lab Demo Site
Field Demo Site
Verification of correct algorithm operationsimulation sequences planned to test the algorithm in extreme conditions• MV and LV secondary
control
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 58
Lab Demo Site
Field Demo Site
More realistic simulation sequences• MV and LV secondary
control
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 59
Lab Demo Site
Field Demo Site
PV reactive power controllable• LV secondary control
PV real power controllable• LV secondary control
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 60
Lab or Simulation Demo Site
Tertiary controltesting
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 61
Lab or Simulation Demo Site
Dynamic tariff
Market agent and aggregator functionalities
Network reconfiguration and market agent
ideal grid for all
Secondary control
10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 62
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 63
RTDS simulations atTUT laboratory
• RTDS emulates the distribution network
• Real IEDs and a real SAU connected to the simulation
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 64
RTDS simulations atTUT laboratory
• RTDS emulates the distribution network
• Real IEDs and a real SAU connected to the simulation
• The simulation network is a reduced model of the real Unareti LV network
• 6 controllable PV generators (size increased from the real ones)
• Tap changer at the MV/LV-transformer (not available in the real network)
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 65
Time DG output Loading
0 s 100 % MIN
50 s 30 % MIN
230 s 30 % MAX
410 s 100 % MAX
Generation
decreases
Load
increasesGeneration
increases
𝑓 = 𝐶𝑙𝑜𝑠𝑠𝑒𝑠𝑃𝑙𝑜𝑠𝑠𝑒𝑠 + 𝐶𝑐𝑢𝑟Σ𝑃𝑐𝑢𝑟
Operation of the LV secondary control
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 66
Operation of the LV secondary control
Generation
decreases
Load
increases
Generation
increases
Objective function
𝑓 = 𝐶𝑙𝑜𝑠𝑠𝑒𝑠𝑃𝑙𝑜𝑠𝑠𝑒𝑠 + 𝐶𝑐𝑢𝑟Σ𝑃𝑐𝑢𝑟
+ 𝐶𝑡𝑎𝑝𝑛𝑡𝑎𝑝 + 𝐶𝑉𝑑𝑖𝑓𝑓Σ 𝑉𝑖,𝑟𝑒𝑓 − 𝑉𝑖2
ideal grid for all
Testing interactions between MV and LV secondary control
10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 67
1341
1006
603
1512
117
585
60
1070
PL1
PL2
2093
2137
1136
PS0023
PV
2
PV
PV
SS1056
1056
PVPV
PV
PV
MV
LV
1
3
4
5
6
7
8
9
10 11
12
13
14
MV/MV
MV/LV
ideal grid for all
Adverse interactions do not usually occur graded time operation of AVC relays adequate to prevent hunting behaviour
10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 68
Acceptable
voltage range
PV production
0.1 1.0 pu
PV production
1.0 0.5 pu
Voltages restored to
an acceptable level
Voltages too high
Changes in one LV network do not cause significant changes to MV network state MV
network secondary control does not change the set points of MV network primary controllers
Voltage levels above nominal to minimize losses
Reactive powers set to
minimize reactive power transfers
MV/LV tap changer operates
The full capacity of PV unit 14 inverter
used for real power generation
ideal grid for all
Testing interactions between MV and LV secondary control
10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 69
Time Feeding network voltage
0:00 23.0 kV
1:45 23.5 kV
3:45 23.0 kV
5:15 23.3 kV
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 70
RTDS simulations at RWTH laboratory
0545
1464
1073
1341
1006
0468
0827
1354
1340
0603
0952
1056
0732
1462
0297
1190
1070 0749
1180
0585 0937
0870 1143
0604
0060
1187
0987
1136
FD8SC1
OLTC
MV / LV
FD8SC2 FD8SC3
FD7SC1 FD7SC2 FD7SC3
FD3SC1 FD3SC2 FD3SC3
FD2SC1
FD2SCe
FD2SCw
FD1SC1 FD1SCe
FD1SCw
OLTC
HV / MV
1217
1023
1024
0338
0145
1512
0378
0605
1438
0117
Rack 1
Rack 3Rack 2
Rack 4
Feed
er 1
Feed
er 2
Feed
er 3
MV and LV Unareti network modeled in the test scenarios
Rack 2
Rack 1
Rack 3
Rack 4
MV and LV grid model implemented for RTDS simulation
ideal grid for all
RTDS simulations at RWTH laboratory
10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 71
Laboratory Computer IED
Oracle VM (Ubuntu 14.04) VIEDs
SM
PMUs
Analog connection
Grid
Digital connection
Analog connection
Laboratory Computer SAU
Oracle VM (Ubuntu 14.04) PSAU
PostgresSQL
Octave
State estimatorWrite SE results
IDE4L standard RDBMS
Read measurementsRead grid data
Oracle VM (Ubuntu 14.04) SSAU
MMS Client Write SE at SS
Rep
ort w
ith SE at SS
Digital connection
PostgresSQL MMS Server
IDE4L standard RDBMS
SCL file server
IEDRTDSMV IEDRTDSMVgen
Oracle VM (Ubuntu 14.04) VIEDs
PostgresSQL MMS Server
IDE4L standard RDBMS
SCL file server
IEDRTDS IEDRTDSgen
MMS Report
MMS write
MMS Server
SCL file server
Read SE at SS
MMS Client
MMS Report
MMS write
Write measurements
Read set points
Write SE at SSWrite measurements
Read set points
Power Control
Read grid status and forecast
Write control set points
Python
ForecasterRead historian
Read weather forecastWrite power forecast
PostgresSQL
Octave
State estimatorWrite SE results
IDE4L standard RDBMS
Read measurementsRead grid data
Power Control
Read grid status and forecast
Write control set points
Python
ForecasterRead historian
Read weather forecastWrite power forecast
DLMS/COSEM client
DLMS/COSEM readWrite
measurements
C37.118 client
Write measurements
C37.118 reports
• PMUs delivery of synchrophasors of current and
voltage. • Smart Meter
delivery of power, voltage and energy data• 4 virtual IEDs
MMS server developed by RWTH installed IDE4L PostgresSQL database for storing of data
• PSAU State estimation and power control developed
by TUT installed in Octave environment Load and generation forecasters developed by
UC3M installed in Python environment MMS Client developed by Unareti DLMS/COSEM client developed by Unareti OpenPDC client configured by RWTH Postgres SQL Database MySQL Database (for PMU data)
• SSAU State estimation and power control developed
by TUT installed in Octave environment Load and generation forecasters developed by
UC3M installed in Python environment MMS Client developed by Unareti MMS Server developed by RWTH DLMS/COSEM client developed by Unareti OpenPDC client configured by RWTH Postgres SQL Database
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 72
RMS voltage time profiles forLV nodes in Mid-Season weekend day afternoon scenario
Active Power time profiles for LV nodes in Mid-Season weekend day afternoon scenario
Reactive Power time profiles for LV nodes in Mid-Season weekend day afternoon scenario
Operation of the LV secondary control
ideal grid for all
Unareti real network demonstration
10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 73
Secondary substation involved in the LV test
phase
ideal grid for all
Unareti real network demonstration
• No voltage violations as expected
10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 74
ideal grid for all
Unareti real network demonstration
• Reactive power is controlled to minimize losses
10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 75
ideal grid for all
Conclusions on secondary control demonstrations• The algorithms (load and production forecaster, state
estimator, secondary power control) operated correctly together
• The secondary control was able to mitigate congestions and to optimize network state
• Graded time operation of AVC relays is usually adequate to prevent adverse interactions between LV and MV secondary control
• The implemented optimization algorithm was in some cases too slow commercial solver should be used
10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 76
ideal grid for all
Tertiary control
10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 77
ideal grid for all
Tertiary control operates only at MV level
10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 78
PL1PL2
PS0023
Load type Power factor Fixed Flexible
Domestic 0.9 59% 41%
Non-domestic (LV) 0.9 53% 47%
MV load 0.95 53% 47%
Type of flexibility Flexibility price (€/kWh)
Domestic consumers 0.15
Non-domestic consumers 0.12*
MV consumers 0.09*Obtained by interpolation.
Assumptions in the market agent
calculations:
ideal grid for all
Operation of network reconfiguration algorithm
• The first section of feeder 1 between nodes PS0023 and 545 is loaded at 102.5 % of its nominal capacity.
• Network reconfiguration algorithm operates and shifts part of the load of feeder 1 to feeder 2 by opening the breaker 468-827 and closing the breaker 603-117
10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 79
Branch loading 102.5%
After reconfiguration
ideal grid for all
Operation of the market agent algorithm
• Line section at the beginning of feeder 3 between nodes PL2 and 1056 is loaded at 104.24 % of its nominal capacity
• Market agent algorithm purchases flexibility products to mitigate the congestion
10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 80
Branch loading 104.24%
Node Flexibility (kW)
60 26.4
297 15.1
585 3.7
604 6.1
732 6.2
749 11.1
870 7.2
937 1.2
987 39.2
1056 13.7
1070 18.6
1136 31.2
1143 7.8
1180 21.3
1187 3.9
1190 1.5
1462 6.2
2236 0.9
ideal grid for all
Also economical evaluation is needed
• Demonstrations verify the correct operation of the implemented automation architecture and algorithms but do not tell anything on the cost-efficiency of alternative methods also network planning methods have to be developed
• Congestion management affects both CAPEX and OPEX• Yearly operational costs of alternative methods can be calculated
using hourly load flow calculations (losses, cost of curtailed generation etc.)
• Investment costs of alternative methods consist of network reinforcement costs and/or costs of automation system
• The network total costs can be compared by combining the investment cost annuities and yearly operational costs
10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 81
ideal grid for all 10/04/2017 WWW.IDE4L.EU – ISGT Europe tutorial October 9th 2016SLIDE 82
• Active Network Management concept
• Distributed automation system
• Congestion management concept
• Demonstrations
• Conclusions
ideal grid for all
Results
SLIDE 83
1. Active network management concept
2. Hierarchical and decentralized automation architecture
3. Distribution grid and DER management functionalities
4. Benefits and impacts of functionalities for DSO
5. Demonstrations of concept, architecture and functionalities in three field demonstrations
6. Recommendations and roadmap
10/04/2017 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016
ideal grid for all
Substation Automation Unit
10/04/2017 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016SLIDE 84
SAU
Interfaces
Database
Applications
DLMS/COSEM
MMS
Prosumers – Smart meters and DER IEDs
Control Center - DMS
Substations - IEDs
IEC 61850
CIMManagement
model
Bridge model
State Estimation
Power control
ForecastData Acquisition
Reports
ideal grid for all
Conclusions
• Basis for distributed grid management and interaction of business players
• Design, implementation and demonstration of ANM, hierarchical and distributed automation architecture and commercial aggregator concepts
• Efficient utilization of grid assets• Monitoring and control of complete grid
• Increased hosting capacity for RESs and DERs
• Enhanced reliability of power supply
• Planning tools estimate the hosting capacity increment
10/04/2017 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016SLIDE 85
ideal grid for all
Conclusions
• Scalability of automation solution• Automation is based on existing devices allows to
gradually deploy the new solutions
• The same architecture and cores of the automation are suitable for both primary and secondary substations
• Functions can be deployed locally and coordinated
• Local functions are light, makes integration scalable
• Vertical and horizontal integration provides a complete view of the distribution network status
• Data exchange between DSO and aggregator to validate, purchasing and activating flexibilities will further extend ANM capabilities
10/04/2017 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016SLIDE 86
ideal grid for all
Conclusions
• Utilization and development of standards • IEC61850, DLMS/COSEM (IEC 62056) and CIM (IEC
61970/61968) for architecture and implementation
• The interoperability has been achieved through:• Identification of interfaces and information exchange
synthesized from the IDE4L use cases.
• The automation architecture was hence derived and defined based on the SGAM framework.
• Implementations of automation system have been demonstrated in three demonstration sites
10/04/2017 WWW.IDE4L.EU – ISGT Europe 2016 tutorial October 9th 2016SLIDE 87