Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/97677
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dc.contributorDepartment of Electrical Engineeringen_US
dc.creatorShi, Men_US
dc.creatorWang, Hen_US
dc.creatorLyu, Cen_US
dc.creatorXie, Pen_US
dc.creatorXu, Zen_US
dc.creatorJia, Yen_US
dc.date.accessioned2023-03-09T07:42:33Z-
dc.date.available2023-03-09T07:42:33Z-
dc.identifier.urihttp://hdl.handle.net/10397/97677-
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.rights© 2021 The Author(s). 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/).en_US
dc.rightsThe following publication Shi, M., Wang, H., Lyu, C., Xie, P., Xu, Z., & Jia, Y. (2021). A hybrid model of energy scheduling for integrated multi-energy microgrid with hydrogen and heat storage system. Energy Reports, 7, 357-368 is available at https://doi.org/10.1016/j.egyr.2021.08.037en_US
dc.subjectDegradation costen_US
dc.subjectEnergy schedulingen_US
dc.subjectHydrogen energy storage systemen_US
dc.subjectMulti-energy microgriden_US
dc.subjectWeighed-MPCen_US
dc.titleA hybrid model of energy scheduling for integrated multi-energy microgrid with hydrogen and heat storage systemen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage357en_US
dc.identifier.epage368en_US
dc.identifier.volume7en_US
dc.identifier.doi10.1016/j.egyr.2021.08.037en_US
dcterms.abstractTo increase the energy utilization efficiency, it becomes fairly promising to convert the surplus electricity from renewable generation to other forms of energy for multi-dimensional consumption. In this paper, we propose a hybrid energy scheduling model for a multi-energy microgrid with the integration of the hydrogen energy storage system (HESS) and the heat storage system (HSS). In our study, the operational uncertainties induced by renewables and loads (including electrical, hydrogen, and heat demand) are comprehensively considered. We investigate such an operating regime that HESS stores the surplus electricity in case of abundant renewable generation and generates electricity through hydrogen fuel cells otherwise. Further, heat units including HESS, combined heat and power (CHP), and external heat suppliers are modeled in this paper. We split the decision-makings of energy scheduling for both the day-ahead stage and real-time stage to tackle the power balancing issues. To effectively solve the aforementioned optimization model, a flexible weighted Model Predictive Control (weighted-MPC) strategy is proposed, in which the receding horizon can be suitably adjusted according to the forecasting accuracy of system uncertainties. The effectiveness of the proposed hybrid model for microgrid energy scheduling is comprehensively verified through extensive case studies.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationEnergy Reports, Nov. 2021, v. 7, p. 357-368en_US
dcterms.isPartOfEnergy reportsen_US
dcterms.issued2021-11-
dc.identifier.isiWOS:000727769100003-
dc.identifier.scopus2-s2.0-85119926511-
dc.identifier.eissn2352-4847en_US
dc.description.validate202303 bcwwen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOS-
dc.description.fundingSourceOthersen_US
dc.description.fundingText2019A1515110901, 2019A1515111173; National Natural Science Foundation of China, NSFC: 72071100; Department of Education of Guangdong Province, DEGP: 2018KQNCX223, G02236002en_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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