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dc.contributor.author | Bordons, C. | es_ES |
dc.contributor.author | Garcia-Torres, F. | es_ES |
dc.contributor.author | Ridao, M.A. | es_ES |
dc.date.accessioned | 2020-07-08T12:36:27Z | |
dc.date.available | 2020-07-08T12:36:27Z | |
dc.date.issued | 2020-07-01 | |
dc.identifier.issn | 1697-7912 | |
dc.identifier.uri | http://hdl.handle.net/10251/147666 | |
dc.description.abstract | [ES] La microrred como elemento agregador de fuentes de generación, cargas y sistemas de almacenamiento de energía aparece como tecnología clave para dotar a los sistemas eléctricos de suficiente flexibilidad para una transición energética basada en fuentes renovables. Sin embargo, el problema de control para la gestión de energía se vuelve complejo cuando se incrementa el número de sistemas conectados a una misma microrred. De igual forma, se requiere flexibilidad para integrar a los vehículos eléctricos. La interacción entre las distintas microrredes y los vehículos hacen necesarias herramientas avanzadas de control para resolver el problema de optimización. El objeto del presente trabajo es presentar distintas herramientas de control predictivo basado en el modelo (Model Predictive Control, MPC) para resolver el problema de control asociado a este tipo de sistemas. En concreto, se abordan dos problemas: la conexión de vehículos eléctricos a la microrred y la interconexión de varias microrredes. Para el primer caso se analizan dos escenarios, según que el intercambio de energía sea uni o bidireccional y se presenta la forma de optimizar la operación usando MPC. En el segundo caso se aborda el problema usando técnicas de control distribuido. | es_ES |
dc.description.abstract | [EN] Microgrids, as aggregators of sources, loads and energy storage systems, appear as key technology to provide the required flexibility to electric power systems to carry out an energy transition based on renewable sources. Nevertheless, the control problem becomes complex when the number of connected components to the same microgrid increases. Also, the system requires flexibility to integrate electric vehicles. The complexity given by the associated control problem to optimize the energy exchange between microgrids and the electric vehicles makes necessary the development of advanced control tools. In this work, dierent Model Predictive Control (MPC) strategies are introduced in order to face the challenge of the control problem formulation of this kind of systems. Specifically, two problems are addressed: the connection of electric vehicles to the microgrid and the interconnection of several microgrids. For the first case, two scenarios are analyzed, depending on whether the energy exchange is uni or bidirectional, the way to optimize the operation using MPC is presented and examples of use are shown. For the second case, the problem isaddressed using distributed control techniques. | es_ES |
dc.description.sponsorship | Este trabajo ha sido realizado parcialmente gracias al apoyo del Ministerio de Econom´ıa, Industria y Competitividad de Espana mediante el proyecto CONFIGURA (DPI2016-78338-R) y por la Comision Europea, en el proyecto AGERAR (0076- ´ AGERAR-6-E), dentro del programa Interreg Spain-Portugal (POCTEP). | es_ES |
dc.language | Español | es_ES |
dc.publisher | Universitat Politècnica de València | es_ES |
dc.relation.ispartof | Revista Iberoamericana de Automática e Informática industrial | es_ES |
dc.rights | Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) | es_ES |
dc.subject | Microgrids | es_ES |
dc.subject | Control of renewable energy resources | es_ES |
dc.subject | Dynamic interaction of power plants | es_ES |
dc.subject | Predictive control | es_ES |
dc.subject | Multiagent systems | es_ES |
dc.subject | Smart grids | es_ES |
dc.subject | Optimal operation and control of power systems | es_ES |
dc.subject | Intelligent control of power systems | es_ES |
dc.subject | Microrredes | es_ES |
dc.subject | Control de recursos de energía renovable | es_ES |
dc.subject | Interacción dinámica de plantas de potencia | es_ES |
dc.subject | Control Predictivo | es_ES |
dc.subject | Sistemas Multi-Agente | es_ES |
dc.subject | Redes Inteligentes | es_ES |
dc.subject | Operación óptima y control de sistemas de potencia | es_ES |
dc.subject | Control inteligente de sistemas de potencia | es_ES |
dc.title | Control predictivo en microrredes interconectadas y con vehículos eléctricos | es_ES |
dc.title.alternative | Model predictive control of interconnected microgrids and electric vehicles | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.4995/riai.2020.13304 | |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//DPI2016-78338-R/ES/CONTROL PREDICTIVO DE MICRORREDES RECONFIGURABLES CON ALMACENAMIENTO HIBRIDO Y MOVIL/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC//0076-AGERAR-6-E/EU//AGERAR/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.description.bibliographicCitation | Bordons, C.; Garcia-Torres, F.; Ridao, M. (2020). Control predictivo en microrredes interconectadas y con vehículos eléctricos. Revista Iberoamericana de Automática e Informática industrial. 17(3). https://doi.org/10.4995/riai.2020.13304 | es_ES |
dc.description.accrualMethod | OJS | es_ES |
dc.relation.publisherversion | https://doi.org/10.4995/riai.2020.13304 | es_ES |
dc.description.upvformatpfin | 253 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 17 | es_ES |
dc.description.issue | 3 | es_ES |
dc.identifier.eissn | 1697-7920 | |
dc.relation.pasarela | OJS\13304 | es_ES |
dc.contributor.funder | European Commission | es_ES |
dc.contributor.funder | Ministerio de Economía y Competitividad | es_ES |
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