Co-shaping the modern electric power system....CEMIE-Redes - Table 5 Technologies for Distribution...
Transcript of Co-shaping the modern electric power system....CEMIE-Redes - Table 5 Technologies for Distribution...
CEMIE-Redes - Table 5
Technologies for Distribution Management
Andrej Souvent, EIMV, Slovenia
CEMIE Workshop, Cuernavaca, September 19th, 2018
Co-shaping the modern electric power system.
Name:Elektroinštitut Milan Vidmar
Milan Vidmar Electric Power Research Institute
Address: Hajdrihova 2, SI - 1000 Ljubljana, SLOVENIA
Web: www.eimv.si
Type: Research institution
Shareholders: Slovenian Academy of Sciences and Arts (100% )
Number of employees:
100
Date of court registration:
1st of June 1948
Quality systems:
ISO 9001 (QMS), ISO14001 (EMS), EN ISO/IEC 17020 (Control Body), EN ISO/IEC 17025
(Testing Laboratory)
Prof. dr. Milan Vidmar
1885-1962
EIMV company profile
Transmission
400 kV
220 kV
(110 kV)
Peak load: 2000 MW
Transmission
MV network (20 kV, 10 kV)
Distribution
Elektro
Celje
Elektro
Maribor
Elektro
Ljubljana
Elektro
Gorenjska
Elektro
Primorska BC
Aobr=174 kW
Transformator
SN/NN 250 kVA
Cca. 11.500 industrial customers (P > 43 kW)
Cca. 900.000 residential and small bussines customers
LV network (0,4kV)
5 DNOs
1 DSO
Main drivers for smart grid
European environmental policy
20% (or even 30%) reduction in CO2 emissions compared to 1990 levels,
20% of the energy, on the basis of consumption, coming from renewables and
20% increase in energy efficiency.
Integration of renewable energy sources
Efficient energy use
Increasing peak load
European Internal Energy Market
Ageing infrastructure
Integration of new technologies (EV charging infrastructure,…)
Enabling new services
New business opportunities
Resilience
Main benefits for distribution
• Better observability and controlabillity
• Cost efficient integration of renewable energy sources and new technologies (EV charging infrastructure, heating – heat pumps,…)
• Better tools for planning and operation
• Optimal utilization of existing infrastructure
• Deferring investments into grid reinforcement
• New services
• Better resilience (microgrids)
• Better assets management
• Better analytics and reporting
• …
Image courtesy of Ventyx/ABBImage courtesy of Alstom Grid
Image courtesy of Schneider Electric Image courtesy of Siemens
Advanced DMS is the key OT system enablingsmart grid adoption in distribution
Which advanced DMS functionsshould be implemented?
Survey results
Network model
Topology Analyzer
Load flow calculations
State estimation
Basic DMS functions:
Outage Management
Classification and reporting
Indexes (SAIDI, SAIFI,…)
Trouble Call Management
Correlator (Lightning)
Fault Management
FLISR
Fault Analayses
Voltage optimization, Volt-Var optimization
Analytiscs and reporting
Performance indicators
Switching order management
Protection coordination
Key advanced functions:
Advanced
DMS
functions
Basic DMS functions
SCADA functions
Advanced Distribution Management System
An example of an advanced function – line
fault correlations due to lightning
In the correlation process the line fault is correlated in real-time with the
lightning location in a certain time and spatial window.
Integrating ADMS with other systems
GIS SCADA ADMS MDMS
Network
analyses tool
Maximo
AMS TCM SCALAR
Relay
protection
management ERP
GIS
SCADA
ADMS
MDMS
Network analyses tool
Maximo AMS
TCM
SCALAR
Relay protection management
ERP
Data drain
Systems
Da
ta s
ou
rce
Sy
stem
s
ADMS requires high quality data from other systems!
An example of an integration matrix:
The Vison of integration
The integration is based on the IEC standards set out in the CEN-CENELC-
ETSI Reference Architecture for European Smart Grids.
The CIM-based integration of technical systems ensures sustainable data
management and enables employees to effectively manage business processes
related to the operation and planning of the power system and asset
management.
Technical systems have a standardized and automatic way to access the data
they need for their operation. Any change of data in one system is also reflected
on other related systems. One of the basic guides is that the data is entered
only in one place - in one system - and updated in all the other systems that are
interested in it.
Data management is built around a consolidated central data repository and
model manager application for modelling the components and related data of
the power grid, with the ability of using simple tools for creating, managing and
using profiles to cover various data exchange needs.
Sustainable data management
The sustainable data management means to set up
appropriate processes and adequate IT support,
which ensures a high level of data consistency,
notwithstanding that changes occur daily, in different
departments and through various systems.
Organizational changes are usually required!
European Commission‘s Mandate M/490
• a standardization mandate to European Standardization
Organizations to support European Smart Grid
• CEN-CENELEC-ETSI Smart Grid Coordination Group (SG-
CG)
In 2012, the SG-CG worked intensively to produce the
following reports:
• Sustainable Processes,
• First Set of Consistent Standards,
• Reference Architecture and on
• Iinformation security and data privacy.https://www.cencenelec.eu/standards/Sectors/SustainableEnergy/SmartGrids/Pages/default.aspx
Mandate M/490
Smart Grid Reference Architecture (SGRA) - technical reference architecture, which
represent the functional information data flows between the main domains and
integrate many systems and subsystem architectures.
First Sets of Standards(FSS) - a set of consistent standards for communication
protocols and data models, which support the information exchange and the
systems integration for common use cases.
The most important elements of the SGRA are:
• European Conceptual Model - a top layer model.
• Smart Grids Architecture Model (SGAM) Framework – a framework supporting
the design of smart grids use cases with an architectural approach allowing for a
representation of interoperability viewpoints in a technology neutral manner.
• SGAM Methodology – a methodology for assessing smart grid use cases and how
they are supported by standards.
Mandate M/490
End 2012, the Smart Grid Mandate M/490 was extended until end 2014.
End 2014, the CEN-CENELEC-ETSI Smart Grid Coordination Group
finalized the following mandated reports:
• Extended Set of Standards support Smart Grids deployment
• Overview Methodology and its annexes:
• General Market Model Development,
• Smart Grid Architecture Model User Manual and
• Flexibility Management
• Smart Grid Interoperability and its Excel tool
• Smart Grid Information Security
Ref.: https://www.cencenelec.eu/standards/Sectors/SustainableEnergy/SmartGrids/Pages/default.aspx
NIST SG conceptual model
Ref.: NIST Framework and Roadmap for Smart Grid Interoperability Standards, Release 2.0, NIST Special Publication 1108R2, februar 2012
EU SG conceptual model
Markets Operations Service providers
Transmission Distrinution Customer
Bulk generationDistributed energy
resources
Mikroomrežja
Domain
Electrical flows
Information flows
Pan-European energy exchange system
Ref.: SG-CG/M490/C_Smart Grid Reference Architecture (Version 3.0), CEN-CENELEC-ETSI Smart Grid Coordination Group, november 2012
Microgrids
GWAC Interoperability stack
CIM
Basic Connectivity
Network Interoperability
Syntactic Interoperability
Semantic Understanding
Business Context
Business Procedures
Business Objectives
Economic/Regulatory Policy
SY
ST
EM
A
SY
ST
EM
B
Business Layer
Functional
Layer
Informational
Layer
Communication
Layer
Component Layer
Tech
nic
al
Info
rmationa
lO
rga
niz
ational
Smart Grid plane - domains and
hierarchical zones
Ref.: SG-CG/M490/C_Smart Grid Reference Architecture (Version 3.0), CEN-CENELEC-ETSI Smart Grid Coordination Group, november 2012
Smart Grids Architecture Model (SGAM)
Ref.: SG-CG/M490/C_Smart Grid Reference Architecture (Version 3.0), CEN-CENELEC-ETSI Smart Grid Coordination Group, november 2012
“Cross-cutting Issues:”
Information security…
Use case mapping process to SGAM
Ref.:: SG-CG/M490/C_Smart Grid Reference Architecture (Version 3.0), CEN-CENELEC-ETSI Smart Grid Coordination Group, november 2012
Sustainable standardization process
Ref.: SG-CG/M490/C_Smart Grid Reference Architecture (Version 3.0), CEN-CENELEC-ETSI Smart Grid Coordination Group, november 2012
IEC 62559-2 template
Example
Bulk generation Transmission Distribution DER Customers
Process
Field
Station
Operation
Enterprise
Market
SCADA DMS
GIS BTP Gredos
RTU
HV MV LV
MDMS
HESFEP
Bulk generation Trasnmission Distribution DER Customers
Process
Field
Station
Operation
Enterprise
Market
IEC 61968-100
IEC 60870-6
IEC 61850
H G
L L
E
Communication technologies for the smart
grid sub-networks
Ref.: SGCG/M490/B_Smart Grid Report First set of standards; v2.0; CEN-CENELEC-ETSI Smart Grid Coordination Group; November 2012
Bulk generation Transmission Distribution DER Customers
Process
Field
Station
Operation
Enterprise
Market
IEC 61970
IEC 61968
IEC 61850-7-4
IEC
61
85
0-8
0-1
IEC
61
85
0-9
0-1
Vision of Smart Grid Implementation in Slovenia (2010)
Slovenian Smart Grid Implementation Roadmap (2012)
National Smart Grid Pilot Project‘s Operational Plan (2013)
New technologies should be pilot tested before being implemented.
National Smart Grid Pilot Project – the Nedo project (2016-2019)
Approach to smart grid implementationin distribution in Slovenia
Slovenian National Smart Grid pilot project
The Slovenian-Japanese NEDO Project is a partnership betweenthe Slovenian transmission system operator (TSO) Eles and theJapanese agency NEDO and its authorised contractor Hitachi,Ltd.
Within the framework of this project, advanced smart gridfunctionalities have been established in order to provide forbetter coordination between stakeholders in the electricitysystem and more efficient operation of the power system.
• I phase of the project started end of 2016
• Project duration is 3 years
• Budget is 36 million € (ELES 15,5 M€ , NEDO 20,5 M€).
Locations and goals of the project
Kleče
ADMS – cloud solution
for 3 DNOs
Substation Slovenj Gradec
50% higher reliability
of supply
Substation Breg
10% lower
peak load < 5% Voltage
violations
Substation Breg1. IntroductionPtuj
10% lower
peak load < 5% Voltage
violations
Idrija municipality
5% lower consumption
in public buildings
1 MW Hybrid battery
1x ADMS (cloud)
3x ADMS DNOs
41x network control devices
5x Local voltage controllers
99x Network measurements
5MW Battery Storage
2x AEMS
100 Relays
150 xEMS
Smart grid functionalitiesDMS (Cloud)
Voltage control Area Energy
Management
Systems
FLISR
Demand
Response
Ancillary
services
Battery
Energy
Storage
Systems
CIM based systems integration
Sytems integration‘s part of the project
European Smart GridReference Architectureshould be followed.
Structural and metering data exchange in accordance with CIM (Common InformationModel) standards.
Real-time data exchange
Smart Grids Architecture Model (SGAM) framework
Elektro Celje DNO
DRCS
SCADA
GIS MDMSNetwork planning tool
Syntactic
moddeling tool
Profiling tool
UML / BPM
modelling tool
Testing tools
Implementation
process support
environment
Integrated
DMS
CIM model
repository
EAM DMS
TSO's
systems
HT
TP
S/S
OA
P
HT
TP
S/S
OA
P
ICC
P (e
xsis
ting)
Middleware according to the IEC 61968-100 (Service bus)
ICC
PTSO
Hitachi
cloud
Use cases which have been implemented:
• Full and incremental network model exchange from GIS to CIM repository and to Integrated DMS
• Network operational state (actual topology) exchange from DMS to GIS
• Metering data exchange from MDMS to Integrated DMS
• DNO – TSO data exchange: metering data of RES production (needed by RES forecast application at TSO)
CIM
DRCS
SCADA/DMS
GIS MDMSNetwork planning tool
Syntactic
moddeling tool
Profiling tool
UML / BPM
modelling tool
Testing tools
Implementation
process support
environment
Integrated
DMS
CIM model
repository
EAM
TSO's
systems
HT
TP
S/S
OA
P
HT
TP
S/S
OA
P
ICC
P (e
xsis
ting)
Middleware according to the IEC 61968-100 (Service bus) – Exsisting platform
ICC
P
TSO
Hitachi
cloud
Elektro Maribor DNO
Use cases which have been implemented:
• Full and incremental network model exchange from CIM model repository to Integrated DMS
• DR related use cases (DRSC – Integrated DMS)
• Metering data exchange from MDMS to Integrated DMS
• Metering data exchange from MDMS to DRSC
• DNO – TSO data exchange: metering data of RES production (needed by RES forecast application at TSO)
CIM
Leasons learned
Data quality must be raised to much higher level (taking
into account also daily changes) to be able to utilize DMS
functionalities at all.
A sustainable infrastructure for the data management
must be implemented.
A cornerstone of such a sustainable infrastructure is an
integration platform which allows for efficient data
exchange between DNO’s systems, like DMS, GIS, MDMS,
Network planning apps, etc.
• 830 consumers joined the project
• 730 consumers receive SMS notice
• 100 consumers have equipment for remote monitoring and activation
installed
Two use cases:
• DSO: Critical peak price tariff
• TSO: agraggation and activation for the ancillary service (tertiary
reserve)
Demand Response in the scope of the Nedo
project
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Activation on 24.1.2018 – normal working day at 19:00
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Activation on 17.2.2018 – Saturday before lunch
An Example – estimating the DR potential
Let's take a primary substation.
Measurements (time series with 15 min. resolutions) for
several years for all secondary substations and distributed
energy resources are available.
Q: For what amount can we lower the annual peak load if 50
hours of demand response activations are available ?
Q: When was the best time for activations?
Big data analyses for the Demand Response
Vir: M. Grabner, A. Souvent, B. Blažič, A. Košir: Statistical Load Time Series Analysis for the Demand Side Management, ISGT EU 2018
Example of data visualization
Ref: M. Grabner, A. Souvent, B. Blažič, A. Košir: Statistical Load Time Series Analysis for the Demand Side Management, ISGT EU 2018
Vir: M. Grabner, A. Souvent, B. Blažič, A. Košir: Statistical Load Time Series Analysis for the Demand Side Management, ISGT EU 2018
Example of data visualization
Example of data visualization
Ref: M. Grabner, A. Souvent, B. Blažič, A. Košir: Statistical Load Time Series Analysis for the Demand Side Management, ISGT EU 2018
Clustering
Ref: M. Grabner, A. Souvent, B. Blažič, A. Košir: Statistical Load Time Series Analysis for the Demand Side Management, ISGT EU 2018
Results
Ref.: M. Grabner, A. Souvent, B. Blažič, A. Košir: Statistical Load Time Series Analysis for the Demand Side Management, ISGT EU 2018
Answer: using 50 hours of demand response anually peak load
can be reduced by 1 MW (5%).
Time and duration of the Critical Peak Price
tariff
Ref: M. Grabner, A. Souvent, B. Blažič, A. Košir: Statistical Load Time Series Analysis for the Demand Side Management, ISGT EU 2018
Information exchange with external partners
This project has received funding from the European Union’s Horizon 2020
research and innovation programme under grant agreement No 774500.
Website: www.tdx-assist.eu
This project aims to design and develop novel ICT tools and
techniques to facilitate scalable and secure data exchange
betweenTSOs and DSOs.
Beyond State-of-the-art Progress:
• Specifications of TSO-DSO information exchange
interfaces based on Use Case analysis and IEC
61970/61968/62325 standards to support highly automated
information exchange.
• Interface specifications for information exchange between
DSOs and market participants based on Use Case analysis
and IEC 61850/62325 standards to support highly
automated information exchanges.
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Beyond State-of-the-art
• A specified suite of ICT protocols and integration
with the defined interfaces.
• Role-based access control that securely accommodates
new data requirements and unbundling processes.
• Proof of Concept using field tests and demonstration
with industry specification at both TSO and DSO levels.
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Expected project outcomes
Andrej Souvent
Head of Electric Power System Control and Operation department
Elektroinštitut Milan Vidmar (EIMV)
(Milan Vidmar Electric Power Research Institute)
Hajdrihova 2, SI-1000 Ljubljana, Slovenija
E-mail: [email protected]
T: +386-1-474-2903