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Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications

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dc.citedby88
dc.contributor.authorHannan M.A.en_US
dc.contributor.authorFaisal M.en_US
dc.contributor.authorJern Ker P.en_US
dc.contributor.authorBegum R.A.en_US
dc.contributor.authorDong Z.Y.en_US
dc.contributor.authorZhang C.en_US
dc.contributor.authorid7103014445en_US
dc.contributor.authorid57215018777en_US
dc.contributor.authorid37461740800en_US
dc.contributor.authorid14007780000en_US
dc.contributor.authorid56608244300en_US
dc.contributor.authorid57191096180en_US
dc.date.accessioned2023-05-29T08:07:25Z
dc.date.available2023-05-29T08:07:25Z
dc.date.issued2020
dc.descriptionCarbon; Decarbonization; Electric energy storage; Fossil fuels; Global warming; Renewable energy resources; Carbon emissions; Decarbonisation; Energy storage system; Method; Microgrid; Optimal energy; Optimization algorithms; Sizing; Storage systems; System sizings; Cost effectivenessen_US
dc.description.abstractCarbon emission from the burning of fossil fuel has resulted in global warming. Climate change and global warming are among the most complex issues requiring immediate solutions. Microgrid (MG) based on renewable energy sources (RESs) can be used to reduce the carbon intensity of electricity and achieve the global decarbonization goal by 2050. Optimizing the size of the energy storage system (ESS) can ensure the sustainable, resilient, and economic operation of the MG. Thus, key features of the optimal ESS, including methods and algorithms of ESS sizing, power quality, reliability, connection mode, and public policy enforcement for low-carbon emission, must be identified. Existing literature mostly focuses on the cost-effective optimal sizing method based on capacity minimization, which overlooks other issues. This work reviews the features of optimal ESS sizing methods and algorithms, their characteristics, and the scenarios between ESS and decarbonization in MG applications to address their shortcomings. ESS characteristics on storage type, energy density, efficiency, advantages, and issues are analyzed. This review highlights details of ESS sizing to optimize storage capacity, reduce consumption, minimize storage cost, determine the optimal placement and mitigate carbon emission for decarbonization. The analyses on the understanding of decarbonization in relation to the use of ESS in MG scenarios are explained rigorously. Existing research gaps, issues, and challenges of ESS sizing for next-generation MG development are also highlighted. This review will strengthen the efforts of researchers and industrialists to develop an optimally sized ESS for future MGs that can contribute toward achieving the decarbonization goal. � 2020 Elsevier Ltden_US
dc.description.natureFinalen_US
dc.identifier.ArtNo110022
dc.identifier.doi10.1016/j.rser.2020.110022
dc.identifier.scopus2-s2.0-85087130223
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85087130223&doi=10.1016%2fj.rser.2020.110022&partnerID=40&md5=6043de07cf68d0d17027d7cb87f77935
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25220
dc.identifier.volume131
dc.publisherElsevier Ltden_US
dc.sourceScopus
dc.sourcetitleRenewable and Sustainable Energy Reviews
dc.titleReview of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applicationsen_US
dc.typeReviewen_US
dspace.entity.typePublication
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