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

43

Activation on 24.1.2018 – normal working day at 19:00

44

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.

54

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.

55

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: andrej.souvent@eimv.si

T: +386-1-474-2903