Dong, S., Kremers, E., Brucoli, M. et al. (2 more authors) (2020) Impact of household heterogeneity on community energy storage in the UK. In: Cruden, A., (ed.) Energy Reports. 4th Annual CDT Conference in Energy Storage & Its Applications, 09-10 Jul 2019, Southampton, U.K.. Elsevier , pp. 117-123.
Abstract
The increasing penetration of Decentralised Energy Resources (DERs) into the residential sector along with a reduction in their subsidy in many countries requires innovative approaches to ensure economic viability. Whilst applications of Household Energy Storage (HES) have been widely investigated and deployed, in recent years communities have been identified as a key scale for energy systems, particularly for energy storage. Community Energy Storage (CES) is therefore a promising alternative deployment model to assist the roll-out of DERs. The power and energy demand may vary significantly with the demographic composition of community; therefore, it is important to evaluate the operation of HES and CES for different communities and hence to assign suitable energy storage options to corresponding objectives. In this work, an Agent Based Model (ABM) is developed that includes household demand heterogeneities, as well as HES and CES, and photovoltaic (PV) systems. The single household models can be aggregated to a community, and hence it is able to simulate the interaction between households in a local, grid connected, energy system. A battery degradation model is also included in order to reproduce the capacity fade of a Li-ion battery over time. The impact on battery performance of the heterogeneous demand within communities is explored using typical performance indicators, such as Self-Consumption Rate (SCR), Self-Sufficiency Rate (SSR) and battery cycle counts.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2020 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Photovoltaics; Lithium-ion battery; Agent-based modelling; Energy system simulation; Community Energy Storage |
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: | 23 Mar 2020 12:08 |
Last Modified: | 03 Jun 2020 16:03 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.egyr.2020.03.005 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:158299 |