akkuvarastojen monitavoitteinen rooli - energiateollisuus · pdf file ·...

LUT – Ville Tikka, 30.1.2018 - Helsinki

Akkuvarastojen

monitavoitteinen rooli

energiajärjestelmässä

Ville Tikka – LUT

2


▪ Project management

− Ville Tikka, Jukka Lassila

▪ Tariffs and grid supporting applications

− Jouni Haapaniemi, Juha Haakana

▪ Optimization and market applications

− Nadezda Belonogova, Arun Narayanan

▪ Hardware and storage control, field tests

− Andrey Lana, Ville Tikka

▪ Supervising professors

− Jarmo Partanen, Samuli Honkapuro

LUT research group and research areas

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Partners and funders:

Sähkötutkimuspooli, STEK, Helen, Helen Electricity Network, Fingrid, Landis+Gyr, LUT

Budget and schedule:

140 k€, 12/2016 – 12/2017

Partners and funding

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Sähkötutkimuspooli


▪ EC currently encourages 1) the increase of efficiency, flexibility, safety,

and power quality in distribution grids and 2) to fully exploit potential

advantages from RES, DG, DR, and Energy Storage Systems

▪ Stationary and mobile BESS play a significant role in modern energy

systems

▪ Multi-objective operation of distributed BESS could lead to lower socio-

economic costs, but might also cause conflicts of interest

Motivation

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Battery Cost Forecasts

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Nykvist, Björn, and Måns Nilsson. "Rapidly falling costs of battery packs

for electric vehicles." Nature Climate Change 5.4 (2015): 329-332.


I. Implementation of control system?

II. How to optimize the stakeholder -specific utilization of an

individual BESS for different purposes (e.g. peak-cutting, control of

frequency and voltage, optimization of reactive power balance,

electricity trade in day-ahead, intraday, and ancillary markets, back-up

power for end-user / network, etc.)?

III. How to optimize the operation of a system with multiple battery

energy storage systems with different sizes, locations, and owners?

The main research questions

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Present project and further questions

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Implementation


Test sites, (build on earlier projects)

Suvilahti, 2016

(Helen)

600 kWh, 1.2 MW

~15 000 LTO Li-ion cells

Green Campus, 2016

LUT

132 kWh, 188 kW

230 pcs LiFePO4

LVDC microgrid, 2014

(Suur-Savon Sähko/LUT)

2x30 kWh, 2x30 kW

2x235 pcs LiFePO4

V2G hybrid, 2014

LUT

1.3kWh, 27 kW (NiMH) + 4.3 kWh, 3 kW (LiFePO4)

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Test sites, (build on earlier projects)

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Distributed

energy storage

(customers)

LVDC

Suomenniemi

Mobile energy

storage

(customers)

LUT Green Campus

Centralized energy

storage

(secondary substation)

LUT Green CampusCentralized energy

storage

(primary substation)

Helen Suvilahti

LUT – Ville Tikka, 30.1.2018 - Helsinki11

Master

unit

LUT Storage &

EV charging

LVDC

Suomenniemi

Helen

Suvilahti


Suomenniemi LVDC research site

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LUT GreenCampus BESS

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EV smart charging

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EN

ST

O

EC

V 1

00

Interface

unit

IEC Master

IEC62196-X, mode 3

Ensto, RS485Ethernet

• Smart charging based on local logic on interface unit

• FCR, power band, peak shaving, etc.


EV smart charging example

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Helen Suvilahti

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• Helsinki Suvilahti

• Connected to 10 kV distribution grid

• Commercial storage utilized in research


SOC, E, Ah,

Restrictions

P, Q

f

P

+fdb+fmax

-fdb -fmax

+Pmax

-Pmax

Data

resources

f, U

Central

control

algorithms

Task 1:

kWh, kW, €

Task 2:

kWh, kW, €

Task 3:

kWh, kW, €

Local control

algorithms

Local control

algorithms

Local control

algorithms

Local control

algorithms

≤ 1 sec,

≤ 15 min

≤ 1 sec,

≤ 15 min

≤ 1 sec,

≤ 15 min

≤ 1 sec,

≤ 15 min

Day,

1h,

15 min

f, U

f, U

f, U

P, Q

P, Q

P, Q

Pref, Eref / Parameters

of the task

Multi-objective control concept for

distributed BESS

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Multi-objective control concept for distributed

BESS (generic control architecture)

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Centralized,

data center /

cloud

computing

Decisions for next n

hours

Distributed on

site

Hardware

control on site

Centralized control

plan execution

Hardware control, U, I,

P, f, etc.Contr

ol syste

m c

om

munic

ation Data resources

• Electricity markets

• Weather forecasts

• Weather observations

• Etc.

Control system level Control system tasks Input data for control

Data resources• Local grid status

• Other locally

observed variables

Data resources• Grid frequency

• U, I, P


Simulation tool: basic structure

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Second-resolutionHour-resolution Year-resolution = techno-economical resultsDay-resolution

Logics SLogics HLogics D Final results

Annual revenues

Operational cost

Profits

Benefit-cost ratio

Return on investment

Strategy to operateTuning input parameters;

Developing optimal bidding and

operational strategy

Input InputInput


Relationship between local and system

tasks

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Conflict of objectives

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Monitoring interface example (campus)

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Monitoring interface example (LVDC site)

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The project outcomes

I. Technical implementation of the control system

I. Fully functioning control architecture

II. Decision making algorithms based on real-time data

III. Visualization platform, etc.

II. Simulation tools developed

I. Enables simulation of different scenarios

II. Based on actual power system and market data

III. Algorithm to analyze conflict of objectives

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Thank you!

Questions?

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Contact:

Ville Tikka

[email protected]

akkuvarastojen monitavoitteinen rooli - energiateollisuus · pdf file ·...

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