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Campo DC | Valor | Lengua/Idioma |
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dc.contributor.author | Montes de Oca, Sebastián | - |
dc.contributor.author | Monzón, Pablo | - |
dc.contributor.author | Belzarena, Pablo | - |
dc.date.accessioned | 2021-04-05T18:26:47Z | - |
dc.date.available | 2021-04-05T18:26:47Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Montes de Oca, S., Monzón, P. y Belzarena, P. Optimal demand side management for the sparse scheduling of smart charge of EVs [Preprint]. EN : 2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA), Montevideo, Uruguay, 28 sep - 2 oct, 2020, pp. 1-6. DOI: 10.1109/TDLA47668.2020.9326178. | es |
dc.identifier.uri | https://hdl.handle.net/20.500.12008/26944 | - |
dc.description | Presentado y publicado en 2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA), Montevideo, Uruguay, 28 sep - 2 oct, pp. 1-6 | es |
dc.description.abstract | In this article, we provide a proof of concept realization of a demand response scheme modelling an EV-aggregator offering smart charging 1 coordination services to several Electric Vehicles (EV). The aggregator model promotes a distributed smart charge coordination of the EVs optimizing energy costs and energy charging profiles. This proposal considers EV's battery health constraints and mobility constraints and promotes spars day-ahead charging profiles. We use a distributed scheme with the main objective of preserving the integrity of the private information of the active agents and scalability issue. The sparsity solution is identified using the alternating direction method of multipliers. The model proposed alternates between promoting sparsity of the charging profile accomplishing EV's constraints and minimizing energy cost. We assume a decentralized communication between the participants of the optimization problem, exchanging adequate signal prices and power profiles keeping the integrity of the private information of each active agent. | es |
dc.description.sponsorship | Agencia Nacional de Investigación e Innovación FSE_1_2017_1_144789 | es |
dc.format.extent | 6 p. | es |
dc.format.mimetype | application/pdf | es |
dc.language.iso | en | es |
dc.rights | Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad de la República.(Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014) | es |
dc.subject | Batteries | es |
dc.subject | Power system stability | es |
dc.subject | Power systems | es |
dc.subject | Optimization | es |
dc.subject | Load management | es |
dc.subject | State of charge | es |
dc.subject | Smart grids | es |
dc.subject | Demand response | es |
dc.subject | Actives agents on the electricity market | es |
dc.subject | Smart Charge for Electric Vehicles | es |
dc.title | Optimal demand side management for the sparse scheduling of smart charge of EVs. | es |
dc.type | Preprint | es |
dc.contributor.filiacion | Montes de Oca Sebastián, Universidad de la República (Uruguay). Facultad de Ingeniería. | - |
dc.contributor.filiacion | Monzón Pablo, Universidad de la República (Uruguay). Facultad de Ingeniería. | - |
dc.contributor.filiacion | Belzarena Pablo, Universidad de la República (Uruguay). Facultad de Ingeniería. | - |
dc.rights.licence | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) | es |
Aparece en las colecciones: | Publicaciones académicas y científicas - Instituto de Ingeniería Eléctrica |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | ||
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MMB20a.pdf | Preprint | 338,69 kB | Adobe PDF | Visualizar/Abrir |
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