towards smart energy systems

Smart Grids Research Unit – Smart RUE

School of Electrical and Computer Engineering

National Technical University of Athens

Towards smart energy systems

Panos Kotsampopoulos, Aris Dimeas, Iasonas Kouveliotis-Lysikatos, Nikos Hatziargyriou

EU HEROES H2020 Solar PV Project Thematic Workshop, CRES, 20th September 2018

Overview

2

Smart Grids

Microgrids

Virtual Power Plants

Integrated Energy Systems (ETIP-SNET)

Research Activities of Smart RUE-NTUA:

o Projects, laboratory and pilot sites

Transition: driving factors

Ambitious European and national targets to promote lower carbon generation, RES and efficient energy use

Increase RES and DG integration into the grids

Need for investment in end-of-life grid renewal (ageing assets)

Handle grid congestion and other technical issues

Increase customer participation

Progress in technology

Energy Management in Microgrids & Non-Interconnected Power Systems

“A Smart Grid is an electricity network that can intelligently integrate the actions of all users connected to it – generators, consumers and those that do both – in order to efficiently deliver sustainable, economic and secure electricity supplies. A SmartGrid employs innovative products and services together with intelligent monitoring, control, communication and self-healing technologies to:

What is a SmartGrid?

•Better facilitate the connection and operation of generators of all sizes and

technologies;

•Allow consumers to play a part in optimizing the operation of the system;

•Provide consumers with greater information and choice of supply;

•Significantly reduce the environmental impact of the whole electricity supply system;

•Deliver enhanced levels of reliability and security of supply.”

Electricity networks of tomorrow

Power flows are bi-directional

Control is being distributed across nodes spread throughout the system


DG, storage, flexible loads

Information and telecommunication systems

A shared vision

Decarbonisation, decentralisation and digitalisation

Flexible: user-centric and designed for the future

Accessible: connect all users

Reliable: security of supply in a digital age

Economic: best value -> innovation, efficiency and

competition


Improved energy efficiency Improvement of energy system reliability, security

and resilience (e.g. monitoring, voltage support, microgrid operation)

Cost efficient electricity infrastructure replacement strategies

Grid renewal: efficient asset management, reduce investment costs

Contribution to peak load reduction

Reduction of the overall energy consumption

Flexible demand for energy, lower prices

Benefits

Active consumers and prosumers

Customers are part of the “network-loop”, both producer and consumer = “prosumer”Real-time price information (smart meters)

Automated systems + convenience (demand reponse)

Adequate investment and reward incentives


https://www.google.gr/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&ved=0ahUKEwj7mMer2vDOAhXBXRQKHSEqDQ0QjRwIBw&url=http://diginomica.com/2015/03/09/uks-smart-meter-rollout-waste-governments-time-money/&psig=AFQjCNFr1PerqTkmChAoRFafCFoZZgkV0g&ust=1472906430929787

https://www.google.gr/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&ved=0ahUKEwjkpbSX2vDOAhWDXBQKHRf5DcQQjRwIBw&url=https://en.wikipedia.org/wiki/Smart_meter&psig=AFQjCNFr1PerqTkmChAoRFafCFoZZgkV0g&ust=1472906430929787

Demand response

Control of residential appliances (e.g. heating, cooling, washing machine)

Comfort level maintained

Active engagement of the consumers

Benefits:

Reduction of electricity cost (e.g. reduction of peak demand -> less generation units connected)

Increase RES integration (e.g. by shifting the consumption at times of high RES production)

Improved power quality (e.g. faster fault detection)

Reduction of energy consumption (monitoring, automated messages etc)

Future Network Vision


Microgrids

Distribution networks with

DG sources, local storage

and controllable loads and

automatic islanding.

Building blocks of smart

grids.

Technical realization of

energy communities.


Microgrids

12

The unique feature of microgrids is that, although

they operate mostly connected to the distribution

network, they can be automatically transferred to

islanded mode, in case of faults in the upstream

network and can be resynchronised after

restoration of the upstream network voltage.

Within the main grid, a microgrid can be

regarded as a controlled entity which can be

operated as a single aggregated load or

generator (e.g. power source, provision of

ancillary services etc)

Virtual power plants

13

Virtual Power Plant (VPP) is an aggregation of

DGs, energy storage elements and controllable

loads accompanied by information and

communication technologies to form a single

imaginary power plant that:

makes contracts in the wholesale market and to

offer services to the system operators

coordinates the power flows of/between its

components to achieve economic, environmental

and technical targets

ETIP-SNET: European Technology & Innovation Platform Smart Networks for Energy Transition

ETIP SNET 2050 Vision

ETIP SNET 2050 VisionA system of systems

Zero energy buildings

Peer to peer energy trading

Integration of electric vehicles

The customer is fully engaged+++

Networks are fully integrated: Electricity

Heating and cooling

Gas

Data

ETIP SNET 2050 Vision

Examples of Research Projects and Activities of

Smart RUE-NTUA

Active Distribution Networks

CL (MV)DG STOR MV)

µG STOR (LV)CL (LV) EV

Hig

h V

olt

age

Med

ium

Vo

ltag

eLo

w V

olt

age

SCADA/DMS

EB

SSC

DTC

OLTC CAP (MV)

OLTCSTOR (DT)

HEM

Development of advanced control concepts of distribution networks:

Load & RES forecast State estimation Optimum operation

(voltage control, losses etc)

DG and storage management

Protection

Testing of coordinated voltage control of distribution networks

The controller:

receives measurements

from various nodes of the

network

Performs an optimization

(voltage deviations,

losses, tap changes)

Sends Q setpoints to the

DG units, P-Q to the

storage and tap changes

to the OLTC

Laboratory validation of the

controller operation

Testing of coordinated voltage control of distribution networks

21

Voltage of all nodes without voltage control Voltage of all nodes with Coordinated Voltage Control

Virtual Power Plant Platform

22

Virtual Power Plant Platform

Software package: forecast of wind farm

and PV generation, loads

Numerical weather forecastSKIRON

Real-time measurements

RBF Neural

NetworksOff-linetraining

INPUT DATA

1st level

Clu

ste

r 1

Clu

ste

r 2

Clu

ste

r 3

Clu

ste

r M

…..

RB

F 1

RB

F 1

RB

F 2

RB

F 1

RB

F 2

RB

F 2

RB

F 1

RB

F K

3

RB

F 2

RB

F K

2

RB

F K

1

RB

F K

M

….. ….. …..…..

Linearfunction

Linearfunction

Linearfunction

Linearfunction

Weighted average

2nd level

3rd Level

4th Level

…..

Multi-layer RBF

Neural Network

On-linetraining

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•201409091700 4216 4456 4606

•201409091700 35183772 3941

•201409091700 30723308 3465

W/FANEMOS

ALKYONIS

Necessary for:• Optimum integration of RES• Dispatch of Power units • Energy market• Solving congestions etc

Energy Management and Efficiency Software

Package for non-interconnected islands

Forecasting of Load Consumption and RES production

Optimization/ Unit Commitment/ Scheduling

Dynamic security monitoring

Monitoring of Energy Efficiency with statistical and mathematical indices

User friendly graphic environment, etc.

Electric Vehicles & grid integration

• New load is added from EVs during Peak Loadmoments

• If the integration of EVs is performed withoutplanning this can lead to early investments fornetwork reinforcement.

• Load management systems for electric vehicles arenecessary

• EVs can help increasing RES penetration intodistribution grids by charging during hours withincreased RES generation.

• Prototype EV Charging Station developed byNTUA

The NTUA laboratory

Meltemi camp: field test site

A few km from Athens

RES, storage, diesel generator

Intelligent load controllers developed by NTUA

Demand response, flexibility market, ancillary services etc

Watch Video: https://www.youtube.com/watch?v=gGoSA4PTykU

*Received award by the «European Smartgrid Technology Platform»

https://www.youtube.com/watch?v=gGoSA4PTykU

Load: 12 houses connected on a single phase 230 Vac grid. Generation: 5 PV units connected via standard grid-tied inverters.

A 9 kVA diesel genset (for back-up).Storage: Battery (60 Volt, 52 kWh) through 3 bi-directional inverters operating

in parallel. Monitoring: Data logging equipment

Microgrid in Gaiduromantra – Kythnos Island

(CRES, NTUA ++ EU project)

This project has received funding from the European Union’s Horizon 2020research and innovation programme under grant agreement No 764452

Solar PV on the Distribution Grid: Smart Integrated Solutions of Distributed Generation based on Solar PV, Energy Storage Devices and Active Demand Management

iDistributedPV31

Carried out by 12 European partners 6 countries : Germany, Greece, Italy, Lithuania, Poland,

and Spain.

Funded by the European Union’s Horizon 2020 research andinnovation programme under grant agreement No 764452

Duration is 30 months, starting in September 2017, and finishingMarch 2020.

APPA

Kostal

Deloitte

IEN

EneaOperator

Exide

Fraunhofer

ICCS-NTUA

HEDNO

LEI

Renerga

Novareckon

iDistributedPV32

• Development of integrated solutions to enhance large penetration of solar PV distributed generation(e.g. households/larger buildings/park areas) with regard to market criteria.

• Develop the concept of “prosumer” using solar PV, energy storage equipment and smart technologiesthat allow to carry out active demand management.

• Solutions will include solar PV generation, solar energy production equipment, inverters, storagedevices, smart technologies, active demand management approaches, monitoring strategy and procedures, grid operation procedures and criteria, and regulatory models.

• Propose effective approaches for the integration of these solutions with the rest of the electricitysystem

iDistributedPV33

iDistributedPV simulation & evaluation framework

Recommendations:

• Classification of

solutions

• Best practices

identification/

most promising

approaches

• Reference values

• Regulatory

recommendation

s

• Technical

specifications

for

manufacturers

and R&D

providers

• Business models

Project: DRES

integration in

distribution

Technical

characteristics:

grid parameters

and topology,

DRES behavior

parameters

demand profile,

energy flows, …

Economics:

revenues model

(incomes and

avoided costs),

investments,

O&M, balancing

costs,…

Project: DRES

integration in

distribution

Technical

characteristics:

grid parameters

and topology,

DRES behavior

parameters

demand profile,

energy flows, …

Economics:

revenues model

(incomes and

avoided costs),

investments,

O&M, balancing

costs,…

Solar PV integration

in distribution grids

Technical

characteristics:

grid parameters

and topology,

solar PV behavior

parameters, solar

PV equipment and

components,

energy storage ,

demand profile

and active

management, ,

energy flows, etc

Economics:

revenues model

(incomes and

avoided costs),

investments, O&M

costs, balancing

costs,…

Assessment

methodology

based on

KPIs

Best

practices

Case studies: Spain, Poland,

Greece, Germany and Lithuania

Different solar PV profiles and

different demand profiles and

different regulatory frameworks

iDistributedPV Simulation & Evaluation

environment: technical and economic

assessment

• Customized

according to

security criteria

defined in

methodology:

voltage,

overload of

circuits,

frequency

controls,

contingency

criteria, etc

• Security

assessment.

• Customized

according to

economic KPIs

• Economic

assessment.

iDistributedPV

assessment:

• Technical

performance

• Technical

requirements

for equipment

and

components

• Integration

approaches

• Strategies and

procedures:

control and

monitoring,

and

management

• Integration

level

• Economic

performance

Power energy

flows

assessment

tool

Economic

assessment tool

customizing

Conclusions

The smartification of networks is necessary to

increase RES integration and promote the energy

transition to a low carbon society

Fundamental concepts and recent developments

were presented

Ongoing and past work of Smart RUE of NTUA in

this field was reported

www.smartrue.gr

Thank you for your attention!

towards smart energy systems

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