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A multimicrogrid energy management model implementing an evolutionary game-theoretic approach

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A multimicrogrid energy management model implementing an evolutionary game-theoretic approach

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Nombre: Aguila-Leon;Chiña ...
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dc.contributor.author Aguila-Leon, Jesus es_ES
dc.contributor.author Chiñas-Palacios, Cristian es_ES
dc.contributor.author García, Edith X. M. es_ES
dc.contributor.author Vargas-Salgado, Carlos es_ES
dc.date.accessioned 2021-03-12T04:31:28Z
dc.date.available 2021-03-12T04:31:28Z
dc.date.issued 2020-11 es_ES
dc.identifier.uri http://hdl.handle.net/10251/163761
dc.description.abstract [EN] Microgrids (MGs) are widely increasing to manage unequal electrical load requirements based on the infrastructure. The goal of this article is to manage energy in a centralized controller multimicrogrid (MMG) system operated at islanded mode. Renewable energy fluctuations in MG due to weather conditions build oscillation in MG operation modes. To solve this, a three-stage energy management MMG system is proposed. The proposed system is composed of operating mode prediction by measuring the weather conditions. In islanded mode, energy management is incorporated using a two-round fuzzy-based speed (TRFS) algorithm followed by evolutionary game theory and status updating by Markov chain. The TRFS algorithm takes into account voltage, frequency, power factor, total harmonic distortion, and loss of produced power probability parameters. The parallel processing of the TRFS algorithm reduces processing time, then a Stackelberg game with a quasi-oppositional symbiotic organisms search approach is carried out for power exchange. Markov chain based future prediction of MG states ensures detection of MG operating mode along with weather changes. Simulations are developed in MATLAB Simulink, and their outcomes show better performance than previous work whose results are evaluated in terms of load and generator output at two modes, power generated at individual MG and exchanged power. es_ES
dc.description.sponsorship Consejo Nacional de Ciencia y Tecnologia, Grant/Award Number: 486670 es_ES
dc.language Inglés es_ES
dc.publisher Wiley es_ES
dc.relation.ispartof International Transactions on Electrical Energy System es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Distributed generation es_ES
dc.subject Energy management es_ES
dc.subject Evolutionary game theory es_ES
dc.subject Microgrid es_ES
dc.subject Multimicrogrid es_ES
dc.subject Optimization es_ES
dc.subject.classification INGENIERIA ELECTRICA es_ES
dc.title A multimicrogrid energy management model implementing an evolutionary game-theoretic approach es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1002/2050-7038.12617 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/CONACyT//486670/ es_ES
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Eléctrica - Departament d'Enginyeria Elèctrica es_ES
dc.description.bibliographicCitation Aguila-Leon, J.; Chiñas-Palacios, C.; García, EXM.; Vargas-Salgado, C. (2020). A multimicrogrid energy management model implementing an evolutionary game-theoretic approach. International Transactions on Electrical Energy System. 30(11):1-19. https://doi.org/10.1002/2050-7038.12617 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1002/2050-7038.12617 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 19 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 30 es_ES
dc.description.issue 11 es_ES
dc.identifier.eissn 2050-7038 es_ES
dc.relation.pasarela S\417837 es_ES
dc.contributor.funder Consejo Nacional de Ciencia y Tecnología, México es_ES
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