On Thursday 19 November 2015, the British Embassy in Paris hosted a second trilateral workshop with French, German and British delegates from the research, government and business sectors to discuss the importance of energy storage.

1. Research-based demo projects – UK
Dr Neal Wade
Newcastle University
neal.wade@ncl.ac.uk

2. Content
• Latest wave of UK grid connected energy storage research
– Survey of UK energy storage demonstrators
• Case studies
– Technical objectives
– Commercial objectives
– Regulatory conditions
• Ongoing role of university research

3. Latest wave of UK storage research
Hemsby 11kV grid connected storage
• AuRA-NMS : Jan 2007 – Jun 2010, then First Low Carbon
Network Fund project: Sep 2010 – Oct 2013
http://innovation.ukpowernetworks.co.uk/innovation/en/Projects/tier-1-projects/demonstrating-the-benefits-of-short-term-discharge-energy-storage/

4. http://www.electricitystorage.co.uk/

5. DNO storage projects
DNO Energy (MWh) Power (MW) Technology
UKPN 0.2 0.2 Li-ion
UKPN 10 6 Li-ion
SSEPD 3 1 Pb-A
SHEPD 0.5 2 Li-ion
SSE 2.4 0.35 LAES
SSE 0.075 0.075 Li-ion
NPg 5 2.5 Li-ion
NPg 3 x 0.1 3 x 0.05 Li-ion
NPg 2 x 0.2 2 x 0.1 Li-ion
WPD 0.5 0.25 NaNiCl

6. CASE STUDIES
Customer Led Network Revolution (with Northern Powergrid)
Smarter Network Storage (with UK Power Networks)

7. CLNR learning outcomes (LO)
• LO1 – Current, emerging and future customer characteristics
• LO2 – Customer flexibility cost and value
• LO3 – Network flexibility cost and value
• LO4 – Optimum solutions – socio, techno, economic
• LO5 – Embedding learning into Business as Usual for DNOs
http://www.networkrevolution.co.uk/

8. 4
CLNR learning outcomes visualised
Active customer participation
National smart meter
data
CUSTOMER
SOLUTIONS
2
Electrical energy storage
Enhanced automatic
voltage control
Real-time thermal rating
INTEGRATED
NETWORK
TECHNOLOGY
3
Heat pumps Photovoltaic panels Electric vehicles
CUSTOMER TECHNOLOGY
1

9. CLNR Powerflow Management at EES1
02/06/2014 05/06/2014
http://www.networkrevolution.co.uk/

10. Smarter Network Storage (UKPN)
• 6 MW/7.5 MVA/10 MWh of
lithium-ion storage installed in
Leighton Buzzard.
• Primary substation has reached
its MVA limit.
• Conventionally, another
overhead line would be installed.
• Can storage solve the problem
and pay its way?
http://innovation.ukpowernetworks.co.uk/ - search ‘SNS’

11. Demand peak shaving
• System design is constrained by peak demand
• Peak reduction needs sufficient power and energy
• Peak needs to be forecast so energy is available
00:00 03:00 06:00 09:00 12:00 15:00 18:00 21:00 00:00
15
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25
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35
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Time of Day
Demand(MVA)
PS Power
PS Duration
PS EnergyElectricity Demand
Line Rating
5
10
15
20
25
30
35
40
02:00
04:00
06:00
08:00
10:00
12:00
14:00
16:00
18:00
20:00
22:00
Demand(MVA)

12. Service schedule optimisation
3 step approach
1. Peak shaving
2. Commercial service layering
-6
-4
-2
0
2
4
6
0
2
4
6
8
10
Min SOC Max SOC Power Tendered
StateofCharge(MWh)
PowerTendered(MW)
-6
-4
-2
0
2
4
6
0
2
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6
8
10
0:00
2:00
4:00
6:00
8:00
10:00
12:00
14:00
16:00
18:00
20:00
22:00
0:00
StateofCharge(MWh)
PowerTendered(MW)

13. Service schedule optimisation
3 step approach
3. Service valuation and selection
𝐸𝑉 =
𝑖=1
𝑛
𝑃𝑖 𝑉𝑖
Energy value
Availability Fee
Utilization Fee
See Greenwood DM, Wade NS, Heyward N, Mehta P, Papadopoulos P, Taylor PC. Scheduling power and energy resources in
the Smarter Network Storage project. In: 23rd International Conference on Electricity Distribution. 2015, Lyon, France: IET

14. SNS commercial experience
Note that during the period represented here the system was operating under manual control to trial each service.
Optimised service combination may produce differing results.
Data courtesy of UKPN

15. Regulatory framework
• The default treatment of storage as a subset of generation creates uncertainty.
• Unbundling requirements add uncertainty.
• Competition in generation and supply must not be distorted.
• Treatment of import as end consumption under climate change, renewable and
low carbon supplier charges increase operating costs for storage operators.
• Distribution charging methodologies could be inconsistent.
• Optimised connections and distribution charging agreements are needed.
• Categorisation of storage installations under CDCM impact network charges.
• Reactive power capability of energy storage systems is not recognised.
Smarter Network Storage SDRC 9.5 - http://innovation.ukpowernetworks.co.uk/innovation/en/Projects/tier-2-projects/Smarter-Network-
Storage-(SNS)/Project-Documents/SNS_ElectricityStorageRegulatoryFramework_SecondReport_v1.0+PXM+2015-09-30.pdf

16. ONGOING ROLE OF UNIVERSITY RESEARCH
Funding streams
Contribution

17. Funded research
• Ofgem’s Network Innovation projects
• Research Council – Grand Challenges and Capital Investments
• Department of Energy and Climate Change
• Catapults
• Innovate UK

18. Examples of University research
Recipients of EPSRC Capital Grant funding
• Imperial College London
• University of Sheffield
• University of Manchester
• University of Birmingham
• Loughborough University
• University of Warwick
• University of Oxford
• Newcastle University
• … and others

19. AC-grid connected energy storage system
Research interests
Custom real-time control platform
LV city-centre location
Optimising battery performance & life
Prototyping novel control strategies
Techno-economic assessment
Siemens SIESTORAGE
236kW 180kWh with
islanding capability
Contact details: rebecca.todd@manchester.ac.uk or andrew.forsyth@manchester.ac.uk

20. Energy storage test hardware
NH Research 9200 battery tester (four 120V
200A channels and two 40V 600A channels)
ESPEC AR680 environmental chamber (680litre
capacity, +180°C to -70°C range, 100% relative
humidity control)
Contact details: rebecca.todd@manchester.ac.uk or andrew.forsyth@manchester.ac.uk
Research interests
Life cycle performance
Energy storage cell /
module parameterisation

21. Liquid Air pilot plant
Contact details: Prof Yulong Ding y.ding@bham.ac.uk

22. Lithium-titanate battery
Contact details: Dave Stone d.a.stone@sheffield.ac.uk

23. Some other UK facilities

24. Summary of research role in demos
• Experimental design
• Pre-trial modelling
• Trial analysis
– Validation
– Extension
– Extrapolation
– Enhancement
– Generalisation
• Dissemination
0
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15:00 16:00 17:00 18:00
ActivePower(kW)
Time (hh:mm)
P Model P Battery
0
10
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15:00 16:00 17:00 18:00
SOC(%)
Time (hh:mm)
SOC Model SOC Battery
Images show model and reality in VEEEG analysis, from: Lyons PF, Wade NS, Jiang T, Taylor
PC, Hashiesh F, Michel M, Miller D. Design and analysis of electrical energy storage
demonstration projects on UK distribution networks. Applied Energy 2015, 137, 677-691.

25. Research-based demo projects – UK
Dr Neal Wade
Newcastle University
neal.wade@ncl.ac.uk