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Fraunhofer ISE

Design, characterisation and operation strategies of 1 KW all-vanadium redox flow battery

Martin Dennenmoser, Kolja Bromberger, Felix Owald, Karsten Korring, Tobias Schwind, Tom Smolinka, Matthias Vetter

Fraunhofer Institute for Solar Energy Systems ISE

The second International Flow Battery Forum,

Edinburgh - Scotland, 4th, 2011

Fraunhofer ISE

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Introduction to redox flow batteries

Applications

Overview energy losses

Stack design

System description

Measurement results

Smart Redox flow Control

Summary

Agenda

V4+ V3+ V5+ V2+

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General layout of a RFB

Vanadium redox flow batteries:

Decoupling capacity from power

Modular design facilitates different applications

Fast response time

Efficiency >75 % possible

No irreversible cross-over of active mass over the membrane

Long calendar life, cycle stability (> 10.000)

Introduction to redox flow batteries

Fraunhofer ISE

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General layout of a RFB

Vanadium redox flow batteries:

Decoupling capacity from power

Modular design facilitates different applications

Fast response time

Efficiency >75 % possible

No irreversible cross-over of active mass over the membrane

Long calendar life, cycle stability (> 10.000)

storage

Electrochemical converter

Introduction to redox flow batteries

Fraunhofer ISE

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Fields of application:

Off-grid / mini-grid

kW/kWh range

Long term storage

Distribution network

MW/MWh range

Energy management

Industrial

Backup power

Load management

Introduction - application

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System overview

Components of a redox flow storage system

Stack

Pumps

Tanks

Valves

Pipes

Inverter

Controlling

Process technology

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System overview energy losses

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System overview energy losses

For an optimal process/energy efficiency inverter, pump control and stack design has to be optimized.

Energy efficiency of the stack is depending on:

Diffusion through the membrane

Internal shunt currents

Ohmic losses

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Hydraulically in parallel configuration causes

--> internal shunt currents

Stack design

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Hydraulically in parallel configuration causes

--> internal shunt currents

Stack design

Electrolyte is electrically conductive!

Internal shunt currents

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Hydraulically in parallel configuration causes

--> internal shunt currents

It is very important to minimize internal shunt currents

The internal shunt currents effects:

Coulombic efficiency

Self discharge

Operation strategies

Corrosion of the bipole plate

Stack design

Electrolyte is electrically conductive!

Internal shunt currents

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Modelling of internal shunt currents

Appropriate design of manifolds and in/outlet of the cells minimizes the internal shunt currents

But trade off between shunt currents and pressure drop has to be found

Stack design

Electrolyte is electrically conductive!

Internal shunt currents

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Stationary analysis of

Pressure drop

Fluid distribution

Parameter studies of

Porosity, permeability of porous electrodes

Velocity of electrolyte

Geometric design of manifolds

Fluid simulation of a half cell

CFD s imulation of an 700 cm half cell

Pre

ssu

re P

a

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Porosity: 95 %

Velocity: 19 ml/min to 76 ml/min per half cell

Stoichiometric flow rate 1 to 4

700 A/m2 current density

1.6 mol/l vanadium

2.0 mol/l sulfuric acid

Parameter study of electrolyte velocity

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Parameter study of electrolyte velocity

manifold inflow

manifold outflow

porous electrode

Velo

city

(m

/s)

Velocity: 19 ml/min

Stoichiometric flow rate

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Velocity: 38 ml/min

Parameter study of electrolyte velocity

Velo

city

(m

/s)

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Velocity: 57 ml/min

Parameter study of electrolyte velocity

Velo

city

(m

/s)

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Velocity: 76 ml/min

Parameter study of electrolyte velocity

Velo

city

(m

/s)

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Velocity: 76 ml/min

Line plots for velocity magnitude at electrode inflow and outflow

Comparison of fluid distribution at electrode inflow and outflow

Parameter study of electrolyte velocity

Velocity field at electrode inflow

Velocity field at electrode outflow

Velo

city

(m

/s)

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Electrode outflow

Velocity field is homogenous

Electrode inflow

Velocity field is not homogenous

depends strongly on velocity of electrolyte

Velocity field, electrode inflow and outflow

Optimized geometric design of manifolds to reach homogenous velocities at electrode inflow

Line graph: Velocity field, y component (m/s)

0,0

0,5

1,0

1,5

2,0

2,5

3,0

150 200 250100500

X 10-3

X 10-3

4,0

3,5

3,0

2,5

2,0

1,5

1,0

0,5

0,0

150 200 250100500

X

X

19ml/min

38ml/min

57ml/min

76ml/min

19ml/min

38ml/min

57ml/min

76ml/min

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Design of a 1 kW stack

18 cells

700 cm active area

Ca. 1.3 V nominal cell voltage

Max. 800 A/m

Max. charge power 1.6 kW

Flow through electrodes

Electrically in series and hydraulically in parallel

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Design of a 1 kW System

Measuring of

Pressure

Temperature

Single cell voltage

Electrolyte level in the tanks

Balancing of the electrolyte level

Valve control

Pump control

SoC determination over OCV measurement

1 kW redox flow system

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Voltage, current and power curves

cc-cv charging

cc discharging

600 A/m

Initialization plus 4 test cycles

Results power-voltage and current curve

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Influenced by

flow rate

cell design

different SoC in the stack

Homogenous single cell voltages are a sign for a good stack design

Results single cell voltage

1

1,1

1,2

1,3

1,4

1,5

1,6

1,7

0:00 1:12 2:24 3:36 4:48 6:00 7:12 8:24 9:36

duration [h:mm]

vo

ltag

e [

V]

cell 1 cell 3 cell 4 cell 8 cell 10 cell 12 average cell voltage

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Without pumps

Stack disconnected from electrolyte fluid cycle

100 % SoC after 2 h

Deinitialization begins after 15 h

Results single cell voltage self-discharge

0,8

0,9

1

1,1

1,2

1,3

1,4

1,5

1,6

1,7

1,8

0:00 4:48 9:36 14:24 19:12 24:00

duration [h:mm]

vo

ltag

e [

V]

cell 16 cell 12 cell 10 cell 8 cell 6 cell 4 cell 3 cell 2 cell 1

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Energy efficiency around 70 %

Coulombic efficiency > 90%

Voltage efficiency depends on the flow rate

Results with very low flow rate

Results - efficiencies

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System integration in the Messib project - Smart Redox Flow Control

Smart Redox Flow Control:

Battery management system

Interface between EMS, inverter and battery

Overview of the integration in the Solarhaus Freiburg

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Smart Redox Flow Control

Smart Redox Flow Control:

Control loops for devices of redox flow battery

Determination of set points (e.g. inverter, pumps)

Optimization of the process cycle

energy efficiency

Interface with energy management system

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Smart Redox Flow Control

Smart Redox flow Control

Pump control

Charge/

Discharge

controller

SOC forecast

SOC

Determination

Smart Redox Flow Control:

Control loops for devices of redox flow battery

Determination of set points (e.g. inverter, pumps)

Optimization of the process cycle

energy efficiency

Interface with energy management system

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Smart Redox Flow Control

AC-Grid VRB +

PeripheryInverter

Pu

mp

co

ntr

ol

Cu

rre

nt A

C S

et

Me

asu

rem

en

t

va

lue

s

Actual values

SOC-forecast

Power AC Demand

Smart Redox flow Control

Energy

Management

System

(EMS)

Pump control

Charge/

Discharge

controller

SOC forecast

SOC

Determination

Smart Redox Flow Control:

Control loops for devices of redox flow battery

Determination of set points (e.g. inverter, pumps)

Optimization of the process cycle

energy efficiency

Interface with energy management system

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Hardware implemen-

tation

Control algorithm

System validation

Parameter fitting

System modeling

Smart Redox Flow Control - development

Required steps for the development:

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Modelled components:

Inverter

Tanks

Stack

Pipes

Pumps

Reference cell

Smart redox flow control

Smart Redox Flow Control modelling in Modelica

System modelling in Modelica / Dymola

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Electrochemical characteristic:

Voltage according to depth of discharge and current density

Equivalent circuit

Results for discharge mode

Cel

l v

olt

age

[V]

Smart Redox Flow Control modelling in Modelica

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Electrochemical characteristic:

Dynamic of the stack

RC equivalent circuit

Important for control algorithm

Dynamic model of the voltage according to the SoC and the current density

Very fast response time!

Smart Redox Flow Control modelling in Modelica

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Energy loss model out of the inner resistance and coulombic efficiency model

The model shows the losses for charge and discharge according to SoC and the nominal power

SoC forecast

Optimized control strategies with several stacks

System layouts / design

Smart Redox Flow Control simulation in Modelica

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Stoichiometric flow rate depends on current and SOC

SOC difference between stack and tanks should not too large

Current density

600 A/m

discharging

Smart Redox Flow Control pump control

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Smart Redox Flow Control pump control

Stoichiometric flow rate depends on current and SOC

SOC difference between stack and tanks should not too large

Current density

600 A/m

discharging

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Stoichiometric flow rate depends on current and SOC

SOC difference between stack and tanks should not too large

Pump control is important for the energy efficiency of the VRFB

Smart Redox Flow Control pump control

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Stoichiometric flow rate depends on current and SOC

SOC difference between stack and tanks should not too large

Pump control is important for the energy efficiency of the VRFB

SOC Range also influences the energy efficiency

Smart Redox Flow Control SOC range variation

70

70,5

71

71,5

72

72,5

73

5-95 %

10-90 %

15-85 %

20-80 %

25-75 %

30-70 %

35-65 %

40-60 %

45-55 %

SOC Range

S

yste

m [

%]

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Summary

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May the flow be with you, and thank you for your kind attention!

Martin Dennenmoser

Fraunhofer ISE

Heidenhofstr. 2 / 79110 Freiburg / Germany

Ph: +49 761 4588 5682

www.ise.fraunhofer.de

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