dc.contributor.editor | León de Mora, Carlos | es |
dc.creator | Guerrero Alonso, Juan Ignacio | es |
dc.creator | Personal Vázquez, Enrique | es |
dc.creator | Parejo Matos, Antonio | es |
dc.creator | García Caro, Sebastián | es |
dc.creator | García Delgado, Antonio | es |
dc.creator | León de Mora, Carlos | es |
dc.date.accessioned | 2020-04-25T07:50:29Z | |
dc.date.available | 2020-04-25T07:50:29Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Guerrero Alonso, J.I., Personal Vázquez, E.,...,León de Mora, C. (2019). Forecasting Recharging Demand to Integrate Electric Vehicle Fleets in Smart Grids. En C. León de Mora (Ed.), Advanced Communication and Control Methods for Future Smartgrids (pp. 254-). IntechOpen | |
dc.identifier.isbn | 978-1-78984-106-0 | es |
dc.identifier.isbn | 978-1-78984-105-3 | es |
dc.identifier.isbn | 978-1-78923-818-1 | es |
dc.identifier.uri | https://hdl.handle.net/11441/95739 | |
dc.description.abstract | Electric vehicle fleets and smart grids are two growing technologies. These technologies
provided new possibilities to reduce pollution and increase energy efficiency.
In this sense, electric vehicles are used as mobile loads in the power grid. A distributed
charging prioritization methodology is proposed in this paper. The solution is based
on the concept of virtual power plants and the usage of evolutionary computation
algorithms. Additionally, the comparison of several evolutionary algorithms, genetic
algorithm, genetic algorithm with evolution control, particle swarm optimization, and
hybrid solution are shown in order to evaluate the proposed architecture. The proposed
solution is presented to prevent the overload of the power grid. | es |
dc.format | application/pdf | es |
dc.format.extent | 27 p. | es |
dc.language.iso | eng | es |
dc.publisher | IntechOpen | es |
dc.relation.ispartof | Advanced Communication and Control Methods for Future Smartgrids | es |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Smart grids | es |
dc.subject | Vehicle-to-grid | es |
dc.subject | Electric vehicles | es |
dc.subject | Charging prioritization | es |
dc.subject | Electric vehicle fleets | es |
dc.subject | Evolutionary computation | es |
dc.title | Forecasting Recharging Demand to Integrate Electric Vehicle Fleets in Smart Grids | es |
dc.type | info:eu-repo/semantics/bookPart | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
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 Tecnología Electrónica | es |
dc.relation.publisherversion | https://www.intechopen.com/books/advanced-communication-and-control-methods-for-future-smartgrids | es |
dc.identifier.doi | 10.5772/intechopen.88488 | es |
dc.contributor.group | Universidad de Sevilla.TIC150: Tecnología Electrónica e Informática Industrial | es |
dc.publication.initialPage | 254 | es |