Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation
Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation
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Date
2012
Authors
Renan Maciel
Vladimiro Miranda
Mauro Rosa
Antonio Padilha-Feltrin
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Abstract
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.