dc.creator | Rodríguez del Nozal, Álvaro | es |
dc.creator | Gutiérrez Reina, Daniel | es |
dc.creator | Alvarado-Barrios, Lázaro | es |
dc.creator | Tapia Córdoba, Alejandro | es |
dc.creator | Escaño González, Juan Manuel | es |
dc.date.accessioned | 2020-02-14T19:27:44Z | |
dc.date.available | 2020-02-14T19:27:44Z | |
dc.date.issued | 2019-11 | |
dc.identifier.citation | Rodríguez del Nozal, Á., Gutiérrez Reina, D., Alvarado-Barrios, L., Tapia Córdoba, A. y Escaño González, J.M. (2019). A MPC Strategy for the Optimal Management of Microgrids Based on Evolutionary Optimization. Electronics, 8 (11). Article number 1371. | |
dc.identifier.issn | 2079-9292 | es |
dc.identifier.uri | https://hdl.handle.net/11441/93228 | |
dc.description.abstract | In this paper, a novel model predictive control strategy, with a 24-h prediction horizon, is
proposed to reduce the operational cost of microgrids. To overcome the complexity of the optimization
problems arising from the operation of the microgrid at each step, an adaptive evolutionary strategy
with a satisfactory trade-off between exploration and exploitation capabilities was added to the
model predictive control. The proposed strategy was evaluated using a representative microgrid that
includes a wind turbine, a photovoltaic plant, a microturbine, a diesel engine, and an energy storage
system. The achieved results demonstrate the validity of the proposed approach, outperforming
a global scheduling planner-based on a genetic algorithm by 14.2% in terms of operational cost.
In addition, the proposed approach also better manages the use of the energy storage system. | es |
dc.description.sponsorship | Ministerio de Economía y Competitividad DPI2016-75294-C2-2-R | es |
dc.description.sponsorship | Unión Europea (Programa Horizonte 2020) 764090 | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | MDPI | es |
dc.relation.ispartof | Electronics, 8 (11). Article number 1371. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Microgrid | es |
dc.subject | Model predictive control | es |
dc.subject | Evolutionary optimization | es |
dc.subject | Genetic algorithm | es |
dc.title | A MPC Strategy for the Optimal Management of Microgrids Based on Evolutionary Optimization | es |
dc.type | info:eu-repo/semantics/article | es |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ingeniería Eléctrica | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ingeniería Electrónica | |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática | |
dc.relation.projectID | DPI2016-75294-C2-2-R | es |
dc.relation.projectID | (Programa Horizonte 2020) 764090 | es |
dc.relation.publisherversion | https://doi.org/10.3390/electronics8111371 | es |
dc.identifier.doi | 10.3390/electronics8111371 | es |
idus.format.extent | 16 p | es |
dc.journaltitle | Electronics | es |
dc.publication.volumen | 8 | es |
dc.publication.issue | 11 | es |
dc.publication.endPage | Article number 1371 | es |