Journal
ELECTRIC POWER SYSTEMS RESEARCH
Volume 89, Issue -, Pages 100-108Publisher
ELSEVIER SCIENCE SA
DOI: 10.1016/j.epsr.2012.02.018
Keywords
Distributed generation planning; Multi-objective optimization; Evolutionary particle swarm optimization; Genetic Algorithm; Tabu Search
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Funding
- FAPESP [2006/06758-9]
- CNPq [303741/2009-0]
- CAPES [0694/09-6]
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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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