An innovative method for building electricity energy management in smart homes based on electric vehicle energy capacity

dc.authorscopusid55756901000
dc.authorscopusid57223391597
dc.authorscopusid57217170170
dc.authorscopusid58918179300
dc.authorscopusid58669556800
dc.authorscopusid58754662100
dc.contributor.authorDodo,Y.A.
dc.contributor.authorIbrahim,A.O.
dc.contributor.authorAbuhussain,M.A.
dc.contributor.authorBaba Girei,Z.J.
dc.contributor.authorMaghrabi,A.
dc.contributor.authorNaibi,A.U.
dc.date.accessioned2024-09-11T07:43:24Z
dc.date.available2024-09-11T07:43:24Z
dc.date.issued2024
dc.departmentOkan Universityen_US
dc.department-tempDodo Y.A., Architectural Engineering Department, College of Engineering, Najran University, Najran, Saudi Arabia; Ibrahim A.O., Department of Architectural Engineering, College of Engineering, University of Ha’il, Ha’il, Saudi Arabia; Abuhussain M.A., Architectural Engineering Department, College of Engineering, Najran University, Najran, Saudi Arabia; Baba Girei Z.J., Nigerian Building and Road Research Institute, Abuja, Nigeria; Maghrabi A., Urban and Engineering Research Department, The Custodian of the Two Holy Mosques Institute for Hajj and Umrah Research, Umm Al-Qura University, Mecca, Saudi Arabia; Naibi A.U., Graduate School of Education, Department of Architecture (Doctorate-English, Okan Istanbul Universitesi, Istanbul, Turkeyen_US
dc.description.abstractThe surging demand for electricity, fueled by environmental concerns, economic considerations, and the integration of distributed energy resources, underscores the need for innovative approaches to smart home energy management. This research introduces a novel optimization algorithm that leverages electric vehicles (EVs) as integral components, addressing the intricate dynamics of household load management. The study’s significance lies in optimizing energy consumption, reducing costs, and enhancing power grid reliability. Three distinct modes of smart home load management are investigated, ranging from no household load management to load outages, with a focus on the time-of-use (ToU) tariff impact, inclining block rate (IBR) pricing, and the combined effect of ToU and IBR on load management outcomes. The algorithm, a multi-objective approach, minimizes the peak demand and optimizes cost factors, resulting in a 7.9% reduction in integrated payment costs. Notably, EVs play a pivotal role in load planning, showcasing a 16.4% reduction in peak loads and a 7.9% decrease in payment expenses. Numerical results affirm the algorithm’s adaptability, even under load interruptions, preventing excessive increases in paid costs. Incorporating dynamic pricing structures like inclining block rates alongside the time of use reveals a 7.9% reduction in payment costs and a 16.4% decrease in peak loads. In conclusion, this research provides a robust optimization framework for smart home energy management, demonstrating economic benefits, peak load reduction potential, and enhanced reliability through strategic EV integration and dynamic pricing. Copyright © 2024 Dodo, Ibrahim, Abuhussain, Baba Girei, Maghrabi and Naibi.en_US
dc.description.sponsorshipNajran University, NU, (NU/NRP/SERC/12/9); Najran University, NUen_US
dc.identifier.citation0
dc.identifier.doi10.3389/fenrg.2024.1364904
dc.identifier.issn2296-598X
dc.identifier.scopus2-s2.0-85186540285
dc.identifier.scopusqualityQ3
dc.identifier.urihttps://doi.org/10.3389/fenrg.2024.1364904
dc.identifier.urihttps://hdl.handle.net/20.500.14517/6302
dc.identifier.volume12en_US
dc.identifier.wosqualityQ3
dc.language.isoen
dc.publisherFrontiers Media SAen_US
dc.relation.ispartofFrontiers in Energy Researchen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectelectric vehicleen_US
dc.subjectelectricity energyen_US
dc.subjectenergy managementen_US
dc.subjectinclining block rateen_US
dc.subjectsmart homeen_US
dc.subjecttime of useen_US
dc.titleAn innovative method for building electricity energy management in smart homes based on electric vehicle energy capacityen_US
dc.typeArticleen_US
dspace.entity.typePublication

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