Jordán, J.; Palanca Cámara, J.; Martí, P.; Julian, V. (2022). Electric vehicle charging stations emplacement using genetic algorithms and agent-based simulation. Expert Systems with Applications. 197:1-15. https://doi.org/10.1016/j.eswa.2022.116739
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/193710
Title:
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Electric vehicle charging stations emplacement using genetic algorithms and agent-based simulation
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Author:
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Jordán, Jaume
Palanca Cámara, Javier
Martí, Pasqual
Julian, Vicente
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UPV Unit:
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Universitat Politècnica de València. Escuela Politécnica Superior de Gandia - Escola Politècnica Superior de Gandia
Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica
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Issued date:
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Abstract:
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[EN] The increasingly evident incorporation of the electric vehicle in urban environments is an already undeniable change. Electric vehicles are appearing on the market with more autonomy and lower prices, which is ...[+]
[EN] The increasingly evident incorporation of the electric vehicle in urban environments is an already undeniable change. Electric vehicles are appearing on the market with more autonomy and lower prices, which is facilitating the progressive change of the vehicle fleet. However, the electric vehicle brings with it the need to provide enough charging stations distributed throughout the city, so that the autonomy of the vehicle is not a problem. This work presents how a genetic algorithm that analyzes the open data sources of a city is used to propose the most suitable locations for these stations. This proposal is the input for a series of experiments that simulate the impact that has the placement of these stations along the city, in order to measure the benefits of the solution proposed by the genetic algorithm. To do this, an agent-based simulation infrastructure was built around a fleet simulator.
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Subjects:
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Genetic algorithm
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Electric vehicle
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Charging station
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Mobility
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Agent-based simulation
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Copyrigths:
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Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
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Source:
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Expert Systems with Applications. (issn:
0957-4174
)
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DOI:
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10.1016/j.eswa.2022.116739
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Publisher:
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Elsevier
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Publisher version:
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https://doi.org/10.1016/j.eswa.2022.116739
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Project ID:
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info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095390-B-C31/ES/HACIA UNA MOVILIDAD INTELIGENTE Y SOSTENIBLE SOPORTADA POR SISTEMAS MULTI-AGENTES Y EDGE COMPUTING/
info:eu-repo/grantAgreement/GENERALITAT VALENCIANA//ACIF%2F2021%2F259//TECNICAS INTELIGENTES PARA LA OPTIMIZACION Y SOSTENIBILIDAD DE LA MOVILIDAD URBANA/
info:eu-repo/grantAgreement/MICINN//IJC2020-045683-I/
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Thanks:
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This work is partially supported by grant RTI2018-095390-B-C31 funded by MCIN/AEI/10.13039/501100011033 and by "ERDF A way of making Europe''. Jaume Jordan is supported by grant IJC2020045683-I funded by MCIN/AEI/10.1303 ...[+]
This work is partially supported by grant RTI2018-095390-B-C31 funded by MCIN/AEI/10.13039/501100011033 and by "ERDF A way of making Europe''. Jaume Jordan is supported by grant IJC2020045683-I funded by MCIN/AEI/10.13039/501100011033 and by "European Union NextGenerationEU/PRTR''. Pasqual Marti is supported by grant ACIF/2021/259 funded by the "Conselleria de Innovacion, Universidades, Ciencia y Sociedad Digital de la Generalitat Valenciana''.
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Type:
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Artículo
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