Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation
Contribuinte(s) |
Universidade Estadual Paulista (UNESP) |
---|---|
Data(s) |
20/05/2014
20/05/2014
01/08/2012
|
Resumo |
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Processo FAPESP: 06/06758-9 This paper proposes a multi-objective approach to a distribution network planning process that deals with the challenges derived from the integration of Distributed Generation (DG). The proposal consists of a multi-objective version of the well-known Evolutionary Particle Swarm Optimization method (MEPSO). A broad performance comparison is made between the MEPSO and other multi-objective optimization meta-heuristics, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and a Multi-objective Tabu Search (MOTS), using two distribution networks in a given DG penetration scenario. Although the three methods proved to be applicable in distribution system planning, the MEPSO algorithm has presented promising attributes and a constant and high level performance when compared to other methods. (C) 2012 Elsevier BM. All rights reserved. |
Formato |
100-108 |
Identificador |
http://dx.doi.org/10.1016/j.epsr.2012.02.018 Electric Power Systems Research. Lausanne: Elsevier B.V. Sa, v. 89, p. 100-108, 2012. 0378-7796 http://hdl.handle.net/11449/9806 10.1016/j.epsr.2012.02.018 WOS:000304787300012 |
Idioma(s) |
eng |
Publicador |
Elsevier B.V. Sa |
Relação |
Electric Power Systems Research |
Direitos |
closedAccess |
Palavras-Chave | #Distributed generation planning #Multi-objective optimization #Evolutionary particle swarm optimization #Genetic Algorithm #Tabu Search |
Tipo |
info:eu-repo/semantics/article |