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dc.rights.licenseopenen_US
hal.structure.identifierESTIA INSTITUTE OF TECHNOLOGY
dc.contributor.authorSARWAR, Fahad Ali
hal.structure.identifierESTIA INSTITUTE OF TECHNOLOGY
dc.contributor.authorHERNANDO GIL, Ignacio
ORCID: 0000-0002-6868-0685
IDREF: 257382976
hal.structure.identifierESTIA INSTITUTE OF TECHNOLOGY
dc.contributor.authorVECHIU, Ionel
ORCID: 0000-0003-4108-3546
IDREF: 102417741
dc.date.accessioned2025-01-17T09:43:28Z
dc.date.available2025-01-17T09:43:28Z
dc.date.issued2024-08-08
dc.identifier.issn2634-1581en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/204355
dc.description.abstractEnRenewable energy‐based microgrids (MGs) strongly depend on the implementation of energy storage technologies to optimize their functionality. Traditionally, electrochemical batteries have been the predominant means of energy storage. However, technological advancements have led to the recognition of hydrogen as a promising solution to address the long‐term energy requirements of microgrid systems. This study conducted a comprehensive literature review aimed at analysing and synthesizing the principal optimization and control methodologies employed in hydrogen‐based microgrids within the context of building microgrid infrastructures. A comparative assessment was conducted to evaluate the merits and disadvantages of the different approaches. The optimization techniques for energy management are categorized based on their predictability, deployment feasibility, and computational complexity. In addition, the proposed ranking system facilitates an understanding of its suitability for diverse applications. This review encompasses deterministic, stochastic, and cutting‐edge methodologies, such as machine learning‐based approaches, and compares and discusses their respective merits. The key outcome of this research is the classification of various energy management strategy methodologies for hydrogen‐based MG, along with a mechanism to identify which methodologies will be suitable under what conditions. Finally, a detailed examination of the advantages and disadvantages of various strategies for controlling and optimizing hybrid microgrid systems with an emphasis on hydrogen utilization is provided.
dc.language.isoENen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subject.enbuilding microgrids
dc.subject.enenergy management systems
dc.subject.enenergy storage
dc.subject.enhydrogen storage
dc.subject.enoptimization methods
dc.subject.enreinforcement learning
dc.subject.enrenewable energy
dc.title.enReview of energy management systems and optimization methods for hydrogen‐based hybrid building microgrids
dc.typeArticle de revueen_US
dc.identifier.doi10.1049/enc2.12126en_US
dc.subject.halSciences de l'ingénieur [physics]en_US
bordeaux.journalEnergy Conversion and Economicsen_US
bordeaux.page259-279en_US
bordeaux.volume5en_US
bordeaux.hal.laboratoriesESTIA - Rechercheen_US
bordeaux.issue4en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
bordeaux.import.sourcehal
hal.identifierhal-04857136
hal.version1
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exportfalse
workflow.import.sourcehal
dc.rights.ccPas de Licence CCen_US
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Energy%20Conversion%20and%20Economics&rft.date=2024-08-08&rft.volume=5&rft.issue=4&rft.spage=259-279&rft.epage=259-279&rft.eissn=2634-1581&rft.issn=2634-1581&rft.au=SARWAR,%20Fahad%20Ali&HERNANDO%20GIL,%20Ignacio&VECHIU,%20Ionel&rft.genre=article


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