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H2020

This project has received funding from the European Union’s Horizon 2020

research and innovation programme under grant agreement n° 691777

This project has received

funding from the European

Union’s Horizon 2020

research and innovation

programme under grant

agreement n° 691777

2019 2035







Name:Elektroinštitut Milan Vidmar (EIMV)

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)

About EIMV







BSP nBSP 2

Regional Balancing Platform with Common Activation Function for cross-border exchange of aFRR

TSO 1 TSO 2 TSO 3 TSO n

BSP 1

BSP nBSP 2

BSP 1

BSP nBSP 2

BSP 1

BSP nBSP 2

BSP 1

Co

ntr

ol &

M

easu

rem

ent

Bid

din

g

aFR

R R

T d

ata

Bid

din

g

CZC

aFR

R R

T d

ata

Bid

din

g

CZC

aFR

R R

T d

ata

Bid

din

g

CZC

aFR

R R

T d

ata

Bid

din

g

CZC

Co

ntr

ol &

M

easu

rem

ent

Bid

din

g

Co

ntr

ol &

M

easu

rem

ent

Bid

din

g

Co

ntr

ol &

M

easu

rem

ent

Bid

din

g

DR DG BG DR DG BG DR DG BG DR DG BG

FutureFlow architecture







CAF

Regional Balancing Platform

LFC

TSO

BSPs

Regional Balancing Platform, TSO‘s LFC and VPP integration







TSO blocks

CAF

LFCSystem

response

TSO block - Internal structure

Demo site design(core)

ELES

APG

MAVIR

TEL







Demo site implementation

DMZ

matlab

ffmys ffifdb

ffmqb

matrikon-opc

sm

arts

no

ffwsrv

FF control centre

docker

MDI

CORE

mqnmea

MDId

MQTT broker

mqnmead vOPCClient

IEC-104

client

Smartsno

Smartnim

Telegraf

Measurements

Control

Bid

broker

Bids

NginXMQTTmonitor

Bids interface

...

Web Interface

Configurator

module

Retime

module

IEC-104

client

Bids module

Stunnel

Stunnel

NginX

Kapacitor

sm

artn

im

Stunnel

ICCP

GW

AX4ICCPSCADA/EMS

HANA (Cloud)

mqnmeadNMEA

TCP

LP

MQTT/

TLS

NMEA

TCP

M/S

bin

ary

TC

P

LP

MQ

TT

/

TLS

LP

, SA

P-X

ML

MQ

TT

/TL

S

LP

MQTT/

TLS

LP

MQ

TT

/

TLS

LP

MQ

TT

/

TLS

JSON

MQTT/

TLS

JSON

MQTT/

TLS

LP, CIM-XML, SAP-XML

MQTT/TLS

SQL

TCP

SQ

L

TC

P

CIM-XML

MQTT/

TLS

demoandsap

mqxmld

SA

P-X

ML

MQ

TT

/

TLS

SA

P-X

ML

MQ

TT

/

TLS

NMEA, XML, LP

MQTT/TLS

HTML, CSS, JS

HTTPS

SSH

LPMQTT/

TLS

LP

HTTP

LP

HTTP

Ka

pa

cito

r AP

I

HT

TP

LP

HT

TP

IEC

-10

4

TLS

IEC

-10

4

TC

P

NMEA

TCP

OP

C

OP

C

IEC

-10

4

TLS

XM

L

MQ

TT

/

TLS

CAF

Optimization module

Other modulesOther modulesOther modules (1)

(2)

(3)







Demo site visualisation







cyberNOC – Flexibility

Aggregation Platform

Peter Nemček, M.Sc.







• Founded in 2010 in Vienna

• Focused on development and deployment of flexibility aggregation platforms (DR, VPP & VB) and related consultancy services

• Founder of Smart Energy Demand Coalition (now SmartEn)

• Member of ESMIG, ETIP SNET, EU Battery Alliance, BRIDGE

• Research partners: AIT, TU Graz, TU Wien, RSE, EIMV, etc.

• Flexibility innovation partner in several Horizon 2020 projects (Flexiciency, FutureFlow, InteGrid, CrossBow, Magnitude …)

• Commercial operations in aFRR and mFRR balancing markets in Austria and Slovenia

About cyberGRID







Monetizing Flexibilities







cyberNOC dashboard







• Aggregation of DR&DGs from 4 EU MS

• Interfacing with 106 DR&DGs (monitoring and control)

• Forecasting (C&I + RES)

• Automatic marginal bidding

• Interfacing with aFRR market

• Automatic real-time controlling of DR&DGs

FutureFlow aFRR aggregation platform







Improved forecasting

• C&I forecasting:

• Based on weighted historic data

• Separate for weekdays, weekends & holidays

• RES forecasting (3E):

• Numerical Weather Prediction Forecasts (ECMWF, GFS, ICON)

• Advanced power models of wind park & solar plant

• Improve forecast accuracy

• Continuous training against measurements or satellite data

• Day-ahead: train & combine with Analog Ensembles or Gradient Boosting

• Intraday correction: Train Time-Series Model for each horizon independently

C&I Forecasting

RES forecasting (Wind in SLO)

RES forecasting (Solar in RO)







Automatic bidding to regional aFRR market

Enabling automatic energy bidding based on the market rules

1. Create internal merit order based on the DR & DG in the pool

2. Apply the backup policy of VPP operator

3. Select the bid size (market rule)

4. Minimum bid price is calculated (DR & DG marginal costs)

5. Bid price based on the revenue optimization strategy by VPP operator

6. Submitting bids to local TSO to be forwarded to aFRR market

DER

i

12

5

4

Capacity

Ener

gy p

rice

3

Bid 1 Bid 2 Bid 3 Bid 4

Bids are generated every hour automatically







Real-time activation control

Processing of received activation message (setpoint) from the connected TSO and de-aggregating received setpoint for controlling individual DR&DG

Steps:

1. Receive setpoint from local TSO (real-time)

2. Creating internal real-time merit order list (considering: availability, price, … of DR&DGs)

3. De-aggregate incoming setpoint signal (from TSO) to meet the internal merit order list and distribute individual signals (setpoints) to the DR&DG

4. Monitor any deviations of the activated DR&DG and reduce deviations by closed-loop controller

5. Report pool performance data to the TSO for validation purposes

Reducing DR/DG set-point Increasing DR/DG set-point

LOCAL TSO

SETPOINT(realtime)

DEAGGREGATE SETPOINT







Experience and results of integrating active consumers into a virtual power plant

dr. Rok Lacko

Head of Energy Services Development at GEN-I, d.o.o.This project has received






About GEN-I

Trading 4.0Energy

Supply 4.0Energy

Services 4.0







About GEN-I







GEN-I is an aggregator!

Energy

Market

Agregator - VPPBig power plant 1 Big power plant 2 Big power plant X

OLD NEW







WP5 Scope & Objectives

WP5 Pilot tests

Task 5.1 RECRUITING C&I CONSUMERS AND DISTRIBUTED GENERATORS

Subtask 5.1.1 Recruitment of C&I consumers, prosumers and distributed generators

Subtask 5.1.2 Installation of the required hardware and information workshops

Task 5.2 PILOT TESTING WITHIN EACH CONTROL ZONE (USE CASES 1 AND 2)

Task 5.3 PILOT TESTING IN A CROSS BORDER SITUATION (USE CASES 3 AND 4)

Target: „pool of 30 to 45 MW of C&I DR&DG units“ This project has received






Participant acquisition process

Nr. of organisations surveyed

recruitment contacts 730

pos. or neg. reply (Q) 600

flexible potential 200

high potential candidates 33

318 MW

50 MW







FutureFlow – Large scale aFRR pilot

4 TSOs

60+ customers

90+ technical units

50+ MW flexibility

Various technologies

100% real-time automatedpower control

FAT 2-10 min







FutureFlow DR/DG recruitment action planStep nr. Activitiy Goal / Task Responsible 2016 2017 2018 2019

1 Preparation of template contract 1) Template contract legal team

2 Analize and prepare list of potential flex providers

2) List of prospects in 4 countries (AT, SI, HU, RO) sales team

3 Prepare "sales" presentation 3) "Sales" presentation (ppt) sales team4 Send sales presentation to all

potentials on the list of prospects 4) Present FutureFlow5) Alert customer flexibility is new business potential (DR).

sales team

5 Schedule face to face meetings 6) Get face to face meeting date or Present flexibility as new business potential7) Get answers to Short questionnaire

sales team

6 Face to face meetings 8) Convince FutureFlow is trustworthy, competent, innovative9) Convince Flexibility is the future10) Get answers to Flexibility questionnaire

sales team

7 Gathering of fulfilled Flexibility questionnaires

11) Get missing answers to Flexibility questionnaire if not able at face to face meeting12) Analyze answers - identify potential

sales team

8 Invitation to FutureFlow 13) Present contract14) Agree for Prequalification process and get contact person responsible for technology15) Signed LoI (not neccessary)

sales team

9 Technical analysis of customers ("Prequalification process")

17) Technical analysis18) Machine selection19) PQ checklist, PQ report

tech team

10 Signature of contract 20) Signed contract sales team11 Technical meeting with customers

("Worshop for technitians")21) Present system architecture and requirements, 22) installation action plan

tech team

12 Technical integration 23)Feasibility study + tech design24) Wiring diagrams and techincal documentation25) Specifications of hardware setup for individual customers26) Organizing supply of technical equipment27) Setup and configuration of new DR/DG unit in flexibility aggregation platform 28) Coordination and supervision of electrical wiring and installation29) Supporting and consulting customers and their subcontractors with software code for "SCADA" upgrades30) Hardware/software commisioning and signal testing31) Writing technical reports32) Organizing and keeping archives of technical documentation

tech team

13 Pilot testing workshop 33) Present pilot tests34) Agree on dates of testing

tech team

14 Project results worshop 35) Present interim results sales + techteams

15 Keeping up motivation 36) Avoid drop-out from pilot tests37) Manage on-time payments38) Respect customer specifics

sales + tech +accounting







Experiments / results

• More than 300 hours testing in 4 countries over 1 year period

• Results:• Technical: aFRR is feasible, but not trivial

• Economic: VPP is cost efficient and competitive• 1,4 mio€ spent on DR/DGs -> 57.000 €/MW (@24 MW base

availability)

• TESLA‘s 100 MW costs 660.000 €/MW

• New 60 MW gas turbine in TE Brestanica costs 660.000 €/MW







Exploitation and plans?

• Raised customer awareness

• Extented knowledge, know-how, competence

• Upgraded 90+ technical units to aFRR ready

• Confidence for aFRR go-live with DR/DGs







The Lightness of the Future

www.talum.si

Boštjan Korošec, Director of the Energy

Management Dpt. in TALUM d.d. KidričevoThis project has received






Basic information for 2018

Year of establishment, production: 1947 ; 1954

Number of employees: 1.500

Ownership: ELES - 86 %

Primary aluminum: 80.000 t

Recycling: 70.000 t

Net sales revenue: 335 mio EUR

Power – base load: 120 MW

Power – Pot room: 110 MW

Energy consumption: 1,1 TWh

Energy efficiency: 2nd on the World


www.talum.si








Aluminium = Primary + Recycled + Remelting

www.talum.si







Slovenian Power Grid and Innovation

Uroš Salobir,

Director for Strategic Innovation, ELES

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement n° 691777

Thank you

www.futureflow.eu

powerpoint presentation · 2019-10-16 · demo site implementation dmz matlab ffmys ffifdb ffmqb...

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