energy storage - 5: dr neal wade, university of newcastle
TRANSCRIPT
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
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/
http://www.electricitystorage.co.uk/
DNO storage projectsDNO Energy (MWh) Power (MW) TechnologyUKPN 0.2 0.2 Li-ionUKPN 10 6 Li-ionSSEPD 3 1 Pb-ASHEPD 0.5 2 Li-ionSSE 2.4 0.35 LAESSSE 0.075 0.075 Li-ionNPg 5 2.5 Li-ionNPg 3 x 0.1 3 x 0.05 Li-ionNPg 2 x 0.2 2 x 0.1 Li-ionWPD 0.5 0.25 NaNiCl
CASE STUDIESCustomer Led Network Revolution (with Northern Powergrid)Smarter Network Storage (with UK Power Networks)
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/
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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
3Heat pumps Photovoltaic panels Electric vehicles
CUSTOMER TECHNOLOGY
1
CLNR Powerflow Management at EES1
02/06/2014 05/06/2014
http://www.networkrevolution.co.uk/
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’
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
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PS Duration
PS EnergyElectricity DemandLine Rating
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1015
2025303540
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Dem
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Service schedule optimisation
3 step approach1. Peak shaving
2. Commercial service layering
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6Min SOC Max SOC Power Tendered
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Power Tendered (M
W)
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Stat
e of
Cha
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(MW
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Power Tendered (M
W)
Service schedule optimisation
3 step approach3. Service valuation and selection
𝐸𝑉=∑𝑖=1
𝑛
𝑃𝑖𝑉 𝑖
Energy valueAvailability FeeUtilization 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
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
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
ONGOING ROLE OF UNIVERSITY RESEARCHFunding streamsContribution
Funded research
• Ofgem’s Network Innovation projects• Research Council – Grand Challenges and Capital Investments• Department of Energy and Climate Change• Catapults• Innovate UK
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
AC-grid connected energy storage system
Research interestsCustom real-time control platformLV city-centre locationOptimising battery performance & lifePrototyping novel control strategiesTechno-economic assessment
Siemens SIESTORAGE 236kW 180kWh with islanding capability
Contact details: [email protected] or [email protected]
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: [email protected] or [email protected]
Research interestsLife cycle performanceEnergy storage cell / module parameterisation
Some other UK facilities
Summary of research role in demos
• Experimental design• Pre-trial modelling• Trial analysis
– Validation– Extension– Extrapolation– Enhancement– Generalisation
• Dissemination
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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.
