Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation

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Data

2012-08-01

Autores

Maciel, Renan S. [UNESP]
Rosa, Mauro
Miranda, Vladimiro
Padilha-Feltrin, Antonio [UNESP]

Título da Revista

ISSN da Revista

Título de Volume

Editor

Elsevier B.V. Sa

Resumo

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.

Descrição

Palavras-chave

Distributed generation planning, Multi-objective optimization, Evolutionary particle swarm optimization, Genetic Algorithm, Tabu Search

Como citar

Electric Power Systems Research. Lausanne: Elsevier B.V. Sa, v. 89, p. 100-108, 2012.