Dong, S., Kremers, E., Brucoli, M. et al. (2 more authors) (2020) Techno-enviro-economic assessment of household and community energy storage in the UK. Energy Conversion and Management, 205. 112330. ISSN 0196-8904
Abstract
Residential electricity demand is expected to rise in the next few decades due to the electrification of heating and transport. Both European and UK national policies suggest that efforts should be made to reduce carbon emissions and increase the share of renewable energy, an important element of which is encouraging generation, typically PV, in partnership with energy storage systems in the residential sector. The scale of the energy storage system is important, i.e. in individual properties or as a community resource. Many advantages of community energy storage (CES) over household energy storage (HES) have been identified, but the design and operation of CES has received significantly less attention. Most existing research has analysed CES at community level only, but the performance and impact on individual households has yet to be fully explored. In this study an agent-based model is proposed to investigate and analyse CES based on a range of criteria. Results indicate that both HES and CES can significantly reduce the grid peak power import and export, improve the community self-consumption rate (SCR) and self-sufficiency rate (SSR), and contribute to much higher energy saving. Furthermore, optimising the CES capacity leads to more effective use of PV power and better demand localisation during high PV-generation periods. It is found that an important challenge for CES systems is to realise the value of the shared electricity equitably amongst the participants and potentially to seek other revenue streams.
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 subsequently published in Energy Conversion and Management. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Agent-based modelling; Community energy storage; Self-consumption; Photovoltaics; Distributed generation; Battery management |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Chemical and Biological Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 22 Nov 2019 14:46 |
Last Modified: | 16 Dec 2020 01:38 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.enconman.2019.112330 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:153792 |