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Transcript of Power Electronics for Grid Scale Energy...
University of Oxford
Power Electronics for Grid Scale Energy Storage
Getting the most out of your cells
Dr Dan Rogers
Senior Research Fellow, Department of Engineering Science
UKES 2016, Birmingham
1st December 2016
Overview
What is power electronics?
A quick look at how today’s grid-scale storage systems are normally connected to the grid
How ‘more’ power electronics can improve
Reliability
Accessible system capacity
The challenges of control and management of very large numbers of cells
Some hardware and results
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What is power electronics?
“The use of power semiconductor devices to control and convert electrical energy”
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DC
sourceInput filter Power transistors Output filter AC source
Power electronics for grid storage
Suitable for relatively small systems: essentially a ‘scaled up EV’
2.5 V, 20 Ah cells (50 Wh): A 1 MW / 1MWh system needs 20,000 cells
If pack voltage is 500 V then pack is 200s100p and DC bus current is 2 kA
10 cm2 cross section copper wiring and large 𝐼2𝑅 losses throughout the system
Monolithic systems of this scale start to become impractical4
Battery pack DC-DC
converter
(optional)DC-AC
converter Step up
transformer Grid
300-600 Vdc
700 Vdc 400 Vac11 kVac
Statistical modelling of packs
Notation
𝑁 = number of cells in system
𝑐𝑖 = capacity of cell 𝑖
𝐶 = capacity of system
Ideally we would like
𝐶 = 𝑖=1𝑁 𝑐𝑖
But for a naïve series string design
𝐶 = 𝑁min𝑖=1𝑁 𝑐𝑖
𝑐𝑖 varies from cell to cell and from moment to moment*
𝑐𝑖 𝑡 = 𝑐𝑖 0 − 𝑑𝑖𝑡 𝑒𝑖 𝑡
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initial capacity degradation rate
(𝑑𝑖 > 0)
catastrophic failure
(1 → 0 at some 𝑡)
*modelling framework developed in collaboration with Matthias Troffaes (Durham) and Louis Aslett (Oxford)
𝑐𝑖, 𝑑𝑖 and 𝑒𝑖 vary from cell-to-cell:
we assume normal distributions or
parameters in order to model large systems
The problem with large series packs
Cell capacities are fairly tightly distributed at SoL
95% of cells within ±0.1 of mean
Cell degradation is relatively ‘slow’
10% decrease in mean capacity
over lifetime
~90% have more than 0.8
capacity left at EoL
Even at SoL, only ~80% of total cell capacity is available to the system
It’s quite likely we will have only 60% of capacity accessible at EoL
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start: 𝑐 0
end: 𝑐 EoL
end: 𝐶 EoLstart: 𝐶 0
Packing cells into modules
A solution to this problem is to break the system up into small modules that are managed individually
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𝑁 modules in
the system
𝑀 cells in
a moduleSystem contains 𝑀𝑁 cells
But module voltage is only 𝑀𝑉𝑐𝑒𝑙𝑙∴ modules should be connected in series
Module power electronics
provides control over the average
current flowing in each module
The ‘depth’ of modularisation strongly influences lifetime behaviour
If 𝑀 = 1 we achieve complete capacity utilisation
Choosing 𝑀 = 5 gives ~20% gain in EoL capacity
Modularisation gives more predictable EoL capacity
This assumes no ‘random complete failure’ mechanism!
Benefits of modularising a system
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From no
modularisation
to using 𝑀 = 5modules
Start of life
End of life
More benefits of modularisation
Adding random failure makes modularisation even more attractive
Here, probability of cell failure is
0.001
i.e. we expect about 20 cells to fail
over the lifetime of the 20,000 cell
system
Of course, in a real system, maintenance will replace failed cells
But system must not suffer downtime as a result of a single cell (or power electronics) failure
Modularisation of some sort is
required
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𝑀 > 500 produces
very unpredictable
system EoL capacity
End of life
Start of life
Option 1
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Power block 1
Power block 2
Power block M
Module
1.1
Module
2.1
Module
Ns.1
Module
1.Np
Module
2.Np
Module
Ns.Np
Grid
Step-up
transformer
Conventional battery pack
Cell 1
Cell 2
Cell Nc
Module
Option 2
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Module
1.1
Module
2.1
Module
Ns.1
Module
1.Np
Module
2.Np
Module
Ns.Np
Intelligent battery pack
Grid
Medium-
voltage
converter
Option 3
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Phase B Phase C
Cascaded H-BridgeGrid
Module
1
Module
2
Module
Nhb
N
Phase A
Markov models for reliability modelling
Model a system as composed of many components
The model includes all possible system states coupled by transitions that occur as components fail
Chain terminates at system failure
E.g. inability to delivery the rated power or energy
Driven by loss of cells themselves, or loss of access to cells (e.g. because of power converter
failure)
Assumptions and limitations
Failure rate of components is constant in a state
But failure rates can change between states
E.g. as components fail, other components work harder13
Comparing reliability of options 1, 2 and 3
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Higher relative
electronics
reliability
(or cells age)
Higher cell
reliability
Constant
temperature Including
thermal model
Cell failure rate/base failure rate
Syste
m M
TT
F (
ho
urs
)
Hardware
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Lithium titanate
20Ah cells (50 Wh)
12 cells in a 3U case (600Wh)
144 cells
in a rack
(7.2kWh)
System architecture
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Output waveforms
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Output voltage
Grid current
Distributed balancing
The CHB circuit provides ‘free’ balancing at the cell level as well as DC to AC conversion
Balance cells in a module
Balance modules in a bank
Balance banks in a system
This limits the exchange of information at the cell level
c.f. trying to manage 20,000 cells from a
central controller
Power hardware is ‘flat’ but communication
and management functions are ‘layered’
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Balancing video
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Conclusion
Cell-based energy storage systems need a power electronic system of one form or another to exchange power with the grid
Fundamentally to provide bidirectional DC-AC conversion
Perform balancing and deal with cell failure
[typical cell voltage] <<< [grid connection voltage]
Massive series strings are a bad idea
There are more ‘intelligent’ ways to organise a system that give better cell capacity
utilisation and much high reliability
Some power electronics circuits provide ‘direct AC synthesis’
Distributed rather than centralised (or monolithic) converters
There are lots of interesting algorithmic challenges attached to large storage systems
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Related publications
E. Chatzinikolaou; D. J. Rogers, "A Comparison of Grid-connected Battery Energy Storage System Designs," in IEEE
Transactions on Power Electronics, 2016 (in press). doi: 10.1109/TPEL.2016.2629020
E. Chatzinikolaou and D. J. Rogers, "Cell SoC Balancing Using a Cascaded Full-Bridge Multilevel Converter in Battery
Energy Storage Systems," in IEEE Transactions on Industrial Electronics, vol. 63, no. 9, pp. 5394-5402, Sept. 2016. doi:
10.1109/TIE.2016.2565463
E. Chatzinikolaou and D. J. Rogers, "Electrochemical cell balancing using a full-bridge multilevel converter and pseudo-open
circuit voltage measurements," 8th IET International Conference on Power Electronics, Machines and Drives (PEMD 2016),
Glasgow, 2016, pp. 1-6. doi: 10.1049/cp.2016.0259
C. A. Ooi, D. J. Rogers, and N. Jenkins, “Balancing control for grid-scale battery energy storage system” in Proceedings of
the ICE Energy, vol. 168:2, pp. 145-157, 2015. doi 10.1680/ener.14.00041
Whitepaper: “UK Research Needs In Grid Scale Energy Storage Technologies” (Brandon et al.), http://energysuperstore.org
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