Multi-Objective Model for Residential Energy Management in Context of Individual Self-Consumption

UDC.coleccionInvestigación
UDC.departamentoEnxeñaría Industrial
UDC.endPage127
UDC.grupoInvCiencia e Técnica Cibernética (CTC)
UDC.institutoCentroCITIC - Centro de Investigación de Tecnoloxías da Información e da Comunicación
UDC.journalTitleMathematics and Computers in Simulation
UDC.startPage120
UDC.volume231
dc.contributor.authorRamos, Sérgio
dc.contributor.authorRoque, Luís A.C.
dc.contributor.authorGomes, António
dc.contributor.authorSoares, João
dc.contributor.authorCalvo-Rolle, José Luis
dc.contributor.authorVale, Zita
dc.date.accessioned2025-09-02T07:31:58Z
dc.date.available2025-09-02T07:31:58Z
dc.date.issued2024-12-14
dc.description© 2024. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.description.abstract[Abstract] The European Union (EU) strongly urged its member states to take action to establish energy communities. Domestic consumers now have the opportunity to organize themselves to play an active and decisive role in the electricity supply chain and make a solid contribution to an ecological footprint. This work proposes residential energy management, considering renewable resources production (photovoltaic panels) and energy storage systems for individual self-consumption approach and boosting future participation in energy community interactions. A multi-objective optimization model using Biased Random Key Genetic Algorithm (BRKGA) was adapted and implemented to minimize electricity consumption costs and maximize self-consumption usage. An energy storage system with 10 kW was considered to optimize electricity management. Two scenarios were proposed, one considering a residential prosumer with a photovoltaic (PV) power installed value of 3.56kWp and the other with 4.20kWp. The results showed a reduction in electricity consumption between 7 % and 8 % and an increase in self-consumption supported by a battery energy storage system of nearly 50 %. Data from an actual system were used to obtain realistic scenarios.
dc.description.sponsorshipThis work has been partially supported by IACOBUS Program 22/23, applications nº 84 and 81, and the Interreg Atlantic Area Programme through the European Regional Development Fund (EAPA 0019/2022-SAtComm). The authors would also like to express their gratitude to the Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development 10.54499/UIDP/00760/2020 (https://doi.org/10.54499/UIDP/00760/2020). and to the Intelligent Systems Associate Laboratory (LA/P/0104/2020) and 10.54499/UIDB/00760/2020 (https://doi.org/10.54499/UIDB/00760/2020, and 2022.00420.CEECIND/CP1742/CT0001 (https://doi.org/10.54499/2022.00420.CEECIND/CP1742/CT0001) grant.
dc.description.sponsorshipInterreg Atlantic Area; EAPA 0019/2022
dc.identifier.citationS. Ramos, L.A.C. Roque, A. Gomes, J. Soares, J.L. Calvo-Rolle, Z. Vale, Multi-objective model for residential energy management in context of individual self-consumption, Mathematics and Computers in Simulation 231 (2025) 120–7. 10.1016/j.matcom.2024.11.017.
dc.identifier.doihttps://doi.org/10.1016/j.matcom.2024.11.017
dc.identifier.urihttps://hdl.handle.net/2183/45692
dc.language.isoeng
dc.publisherElsevier
dc.relation.urihttps://doi.org/10.1016/j.matcom.2024.11.017
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.accessRightsembargoed access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectEnergy management
dc.subjectOptimization
dc.subjectPhotovoltaic (PV) prosumer
dc.subjectSelf-consumption
dc.titleMulti-Objective Model for Residential Energy Management in Context of Individual Self-Consumption
dc.typejournal article
dc.type.hasVersionAM
dspace.entity.typePublication
relation.isAuthorOfPublication89839e9c-9a8a-4d27-beb7-476cfab8965e
relation.isAuthorOfPublication.latestForDiscovery89839e9c-9a8a-4d27-beb7-476cfab8965e

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