Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/41335
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dc.contributor.authorSilva, Joãopt_PT
dc.contributor.authorFerreira, Joaquimpt_PT
dc.contributor.authorBartolomeu, Paulo C.pt_PT
dc.date.accessioned2024-04-03T12:19:09Z-
dc.date.available2024-04-03T12:19:09Z-
dc.date.issued2023-
dc.identifier.isbn979-8-3503-2476-1-
dc.identifier.urihttp://hdl.handle.net/10773/41335-
dc.description.abstractElectrical energy consumption is steadily growing worldwide, while renewable energy sources are gaining market share. In parallel, energy systems are undergoing a profound transformation, moving from a top-down hierarchical structure to a more decentralized model focused on the consumer, who will also produce, store and sell their own energy. This paper proposes a decision algorithm designed to help with the energy management task, in the context of a grid-connected household, with renewable energy production and electric vehicles (EVs). The algorithm makes use of several inputs such as energy consumption prediction, energy production output, EV battery state, and grid energy price in order to perform the optimal charge and discharge actions. The proposed algorithm was validated in a simulated environment attaining an average decrease of 18.9% in the energy cost of the household.pt_PT
dc.language.isoengpt_PT
dc.publisherIEEEpt_PT
dc.relationCENTRO-01-0247-FEDER-046995pt_PT
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50008%2F2020/PTpt_PT
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F50008%2F2020/PTpt_PT
dc.rightsrestrictedAccesspt_PT
dc.titleHeuristic energy management algorithm for buildings with renewables and vehicle-to-grid chargingpt_PT
dc.typebookPartpt_PT
dc.description.versionpublishedpt_PT
dc.peerreviewedyespt_PT
ua.event.date26-28 July, 2023pt_PT
degois.publication.title2023 IEEE 3rd International Conference on Industrial Electronics for Sustainable Energy Systems (IESES)pt_PT
dc.identifier.doi10.1109/IESES53571.2023.10253729pt_PT
dc.identifier.esbn979-8-3503-2475-4-
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