Pimm, AJ, Palczewski, J orcid.org/0000-0003-0235-8746, Morris, R et al. (2 more authors) (2020) Community energy storage: A case study in the UK using a linear programming method. Energy Conversion and Management, 205. ARTN: 112388. ISSN 0196-8904
Abstract
In this paper, we investigate how energy storage can be used to increase the value of community energy schemes through cost reductions, infrastructure support, increased scheme membership, and reduced carbon emissions. A linear programming optimisation framework is developed to schedule the operation of behind-the-meter energy storage such that costs are minimised, while keeping peak demands within allowable limits. This is also extended to model generation-integrated energy storage systems, where the storage is located in the flow of energy from primary source (e.g. wind) to a usable form (e.g. electricity). To demonstrate the potential of energy storage within a real community energy scheme, we present a case study of a community hydro scheme in North Wales, considering both battery storage and a reservoir-based storage system. It is found that either system can be used to substantially increase the membership of the scheme while avoiding impacts on the electricity network, but that storage remains prohibitively expensive when used for self-consumption of renewables and arbitrage. We also investigate the impacts of energy storage on the community's carbon emissions, showing that storage operation appears to provide very little additional reduction in emissions when grid average emissions factors are used.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 Elsevier Ltd. This is an author produced version of a paper published in Energy Conversion and Management. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Micro hydro; Battery storage; Scheduling; Linear programming |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemical & Process Engineering (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds) |
Funding Information: | Funder Grant number EPSRC (Engineering and Physical Sciences Research Council) EP/N001745/1 EPSRC (Engineering and Physical Sciences Research Council) EP/P022049/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 07 Jan 2020 13:06 |
Last Modified: | 18 Dec 2020 01:38 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.enconman.2019.112388 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:155261 |
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