Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/21974
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dc.contributor.authorXie, C-
dc.contributor.authorWang, D-
dc.contributor.authorLai, CS-
dc.contributor.authorWu, R-
dc.contributor.authorWu, X-
dc.contributor.authorLai, LL-
dc.date.accessioned2020-12-07T15:52:12Z-
dc.date.available2020-12-07T15:52:12Z-
dc.date.issued2020-11-29-
dc.identifierORCID iD: Chun Sing Lai https://orcid.org/0000-0002-4169-4438-
dc.identifier125308-
dc.identifier.citationXie, C. et al. (2021) 'Optimal sizing of battery energy storage system in smart microgrid considering virtual energy storage system and high photovoltaic penetration', Journal of Cleaner Production, 125308, pp. 1 - 17. doi: 10.1016/j.jclepro.2020.125308.en_US
dc.identifier.issn0959-6526-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/21974-
dc.description.abstractIn the smart microgrid system, the optimal sizing of battery energy storage system (BESS) considering virtual energy storage system (VESS) can minimize system cost and keep system stable operation. This paper proposes a two-layer BESS optimal sizing strategy considering dispatch of VESS in a smart microgrid with high photovoltaic (PV) penetration. In the first layer, VESS modelling and aggregation are established, and the initial size of BESS is determined by considering VESS participation in demand response program. In the second layer, the optimal sizing of BESS is studied and the optimal energy resources dispatching strategy is formulated via considering various constraints in the system. The mean-variance Markowitz theory is applied to assess the risk of system cost variability due to the presence of PV and load uncertainties. With the ratio of load varies from 70% to 130%, and PV generation ratio from 40% to 100%, sensitivity analysis reveals the optimal size of BESS is less impacted by PV generation change. Also with VaR(95%) the risk of system cost variability can be further reduced through VESS participation.-
dc.description.sponsorshipDepartment of Finance and Education of Guangdong Province 2016 [202]: Key Discipline Construction Program, China; the Education Department of Guangdong Province: New and Integrated Energy System Theory and Technology Research Group [Project Number 2016KCXTD022]; and Brunel University London BRIEF Funding, UK.en_US
dc.format.extent1 - 17-
dc.format.mediumPrint-Electronic-
dc.languageEnglish-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rightsCopyright © 2020 Elsevier Ltd. All rights reserved. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1016/j.jclepro.2020.125308, made available on this repository under a Creative Commons CC BY-NC-ND attribution licence (https://creativecommons.org/licenses/by-nc-nd/4.0/).-
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/-
dc.subjectbattery energy storage systemen_US
dc.subjecthigh photovoltaic penetrationen_US
dc.subjectoptimal sizingen_US
dc.subjectrisk controlen_US
dc.subjectvirtual energy storage system (VESS)en_US
dc.titleOptimal sizing of battery energy storage system in smart microgrid considering virtual energy storage system and high photovoltaic penetrationen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1016/j.jclepro.2020.125308-
dc.relation.isPartOfJournal of Cleaner Production-
pubs.publication-statusPublished-
dc.identifier.eissn1879-1786-
dc.rights.holderElsevier Ltd.-
Appears in Collections:Dept of Electronic and Electrical Engineering Research Papers

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