Battery Sizing Optimization in Power Smoothing Applications
dc.contributor.author | Zulueta, Asier | |
dc.contributor.author | Ispas-Gil, Decebal Aitor | |
dc.contributor.author | Zulueta Guerrero, Ekaitz | |
dc.contributor.author | Garcia-Ortega, Joseba | |
dc.contributor.author | Fernández Gámiz, Unai | |
dc.date.accessioned | 2022-02-11T19:14:53Z | |
dc.date.available | 2022-02-11T19:14:53Z | |
dc.date.issued | 2022-01-19 | |
dc.identifier.citation | Energies 15(3) : (2022) // Article ID 729 | es_ES |
dc.identifier.issn | 1996-1073 | |
dc.identifier.uri | http://hdl.handle.net/10810/55457 | |
dc.description.abstract | The main objective of this work was to determine the worth of installing an electrical battery in order to reduce peak power consumption. The importance of this question resides in the expensive terms of energy bills when using the maximum power level. If maximum power consumption decreases, it affects not only the revenues of maximum power level bills, but also results in important reductions at the source of the power. This way, the power of the transformer decreases, and other electrical elements can be removed from electrical installations. The authors studied the Spanish electrical system, and a particle swarm optimization (PSO) algorithm was used to model battery sizing in peak power smoothing applications for an electrical consumption point. This study proves that, despite not being entirely profitable at present due to current kWh prices, implanting a battery will definitely be an option to consider in the future when these prices come down. | es_ES |
dc.description.sponsorship | The authors were supported by the government of the Basque Country through research grants ELKARTEK 21/10: BASQNET: Estudio de nuevas técnicas de inteligencia artificial basadas en Deep Learning dirigidas a la optimización de procesos industriales. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | |
dc.subject | swarm optimization | es_ES |
dc.subject | battery sizing | es_ES |
dc.subject | power smoothing | es_ES |
dc.subject | battery management system | es_ES |
dc.title | Battery Sizing Optimization in Power Smoothing Applications | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.date.updated | 2022-02-11T14:46:26Z | |
dc.rights.holder | © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | es_ES |
dc.relation.publisherversion | https://www.mdpi.com/1996-1073/15/3/729 | es_ES |
dc.identifier.doi | 10.3390/en15030729 | |
dc.departamentoes | Ingeniería de sistemas y automática | |
dc.departamentoes | Ingeniería nuclear y mecánica de fluidos | |
dc.departamentoeu | Ingeniaritza nuklearra eta jariakinen mekanika | |
dc.departamentoeu | Sistemen ingeniaritza eta automatika |
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Except where otherwise noted, this item's license is described as © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).