Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation
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Elsevier B.V. Sa
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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.
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Distributed generation planning, Multi-objective optimization, Evolutionary particle swarm optimization, Genetic Algorithm, Tabu Search
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Inglês
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Electric Power Systems Research. Lausanne: Elsevier B.V. Sa, v. 89, p. 100-108, 2012.
