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dc.contributor.author | Rodríguez-García, Javier![]() |
es_ES |
dc.contributor.author | Ribó-Pérez, David Gabriel![]() |
es_ES |
dc.contributor.author | Álvarez, Carlos![]() |
es_ES |
dc.contributor.author | Peñalvo-López, Elisa![]() |
es_ES |
dc.date.accessioned | 2021-07-03T03:30:50Z | |
dc.date.available | 2021-07-03T03:30:50Z | |
dc.date.issued | 2020 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/168715 | |
dc.description.abstract | [EN] Integration of renewable energy sources require an increase in the flexibility of power systems. Demand response is a valuable flexible resource that is not currently being fully exploited. Small and medium industrial consumers can deliver a wide range of underused flexibility resources associated with the electricity consumption in their production processes. Flexible resources should compete in liberalized operation markets to ensure the reliability of the system at a minimum cost. This paper presents a new tool to assist industrial demand response to participate in operation markets and optimize its value. The tool uses a combined physical-mathematical modelling of the industrial demand response and a Parallel Particle Swarm Optimization algorithm specifically tuned for the proposed problem to maximize the profit. The main advantages of the proposed tool are demonstrated in the paper through its application to the participation of a meat factory in the Spanish tertiary reserve market during a whole year using a quarter-hourly time resolution. The enhanced performance of the proposed tool with respect to previous methodologies is shown with these four flexible processes examples, where the maximum available profit obtained in the simultaneous consideration of all different flexible processes is computed. The flexible processes are technical and economically characterized in a way that makes the tool valid for most of the processes in the industry. | es_ES |
dc.description.sponsorship | This work was supported in part by the Primeros Proyectos de Investigacion under Grant PAID-06-18, in part by the Vicerrectorado de Investigacion, Innovacion y Transferencia de la Universitat Politecnica de Valencia (UPV) Valencia-Spain, Generalitat Valenciana through the Research Project under Grant AICO/2019/001, in part by the Spanish Administration under Grant FPU2016/00962, in part by the AEI/10.13039/501100011033 (Ministerio de Ciencia, Innovacion y Universidades, Spanish Government) through the Research Projects under Grant ENE-2016-78509-C3-1-P and Grant RED2018-102618-T, and in part by the EU FEDER Funds. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Institute of Electrical and Electronics Engineers | es_ES |
dc.relation.ispartof | IEEE Access | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Demand response | es_ES |
dc.subject | Energy resource management | es_ES |
dc.subject | Industrial production | es_ES |
dc.subject | End-user tool | es_ES |
dc.subject | Parallel particle swarm optimization | es_ES |
dc.subject.classification | INGENIERIA ELECTRICA | es_ES |
dc.title | Maximizing the Profit for Industrial Customers of Providing Operation Services in Electric Power Systems via a Parallel Particle Swarm Optimization Algorithm | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1109/ACCESS.2020.2970478 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/GVA//AICO%2F2019%2F001/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI//RED2018-102618-T/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/UPV//PAID-06-18/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI//PID2019-106901GB-I00/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//ENE2016-78509-C3-1-P/ES/DESARROLLO DE LA RESPUESTA AGREGADA DE LA DEMANDA MEDIANTE MODELOS IMBRICADOS Y SU INTERACCION CON TECNOLOGIAS DE MEDIDA Y CONTROL EN LOS SECTORES RESIDENCIALES Y COMERCIALES/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MECD//FPU16%2F00962/ES/FPU16%2F00962/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/UPV//SP20180248/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Ingeniería Eléctrica - Departament d'Enginyeria Elèctrica | es_ES |
dc.description.bibliographicCitation | Rodríguez-García, J.; Ribó-Pérez, DG.; Álvarez, C.; Peñalvo-López, E. (2020). Maximizing the Profit for Industrial Customers of Providing Operation Services in Electric Power Systems via a Parallel Particle Swarm Optimization Algorithm. IEEE Access. 8:24721-24733. https://doi.org/10.1109/ACCESS.2020.2970478 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1109/ACCESS.2020.2970478 | es_ES |
dc.description.upvformatpinicio | 24721 | es_ES |
dc.description.upvformatpfin | 24733 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 8 | es_ES |
dc.identifier.eissn | 2169-3536 | es_ES |
dc.relation.pasarela | S\403577 | es_ES |
dc.contributor.funder | Generalitat Valenciana | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |
dc.contributor.funder | European Regional Development Fund | es_ES |
dc.contributor.funder | Universitat Politècnica de València | es_ES |
dc.contributor.funder | Ministerio de Educación, Cultura y Deporte | es_ES |
dc.contributor.funder | Ministerio de Economía y Competitividad | es_ES |
dc.subject.ods | 07.- Asegurar el acceso a energías asequibles, fiables, sostenibles y modernas para todos | es_ES |