Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/1510
Título: Particle swarm optimization based approaches to vehicle-to-grid scheduling
Autor: Soares, João
Morais, H.
Vale, Zita
Palavras-chave: Electric vehicle
Energy resource management
Mixed Integer Non-Linear Programming (MINLP)
Particle swarm optimization
Data: 2012
Editora: IEEE
Resumo: This paper addresses the problem of energy resources management using modern metaheuristics approaches, namely Particle Swarm Optimization (PSO), New Particle Swarm Optimization (NPSO) and Evolutionary Particle Swarm Optimization (EPSO). The addressed problem in this research paper is intended for aggregators’ use operating in a smart grid context, dealing with Distributed Generation (DG), and gridable vehicles intelligently managed on a multi-period basis according to its users’ profiles and requirements. The aggregator can also purchase additional energy from external suppliers. The paper includes a case study considering a 30 kV distribution network with one substation, 180 buses and 90 load points. The distribution network in the case study considers intense penetration of DG, including 116 units from several technologies, and one external supplier. A scenario of 6000 EVs for the given network is simulated during 24 periods, corresponding to one day. The results of the application of the PSO approaches to this case study are discussed deep in the paper.
URI: http://hdl.handle.net/10400.22/1510
ISBN: 978-1-4673-2727-5
Versão do Editor: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6345358
Aparece nas colecções:ISEP – GECAD – Comunicações em eventos científicos

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