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

Author(s)

Maciel, Renan S. ^[1] ; Rosa, Mauro ^{[2, 3]} ; Miranda, Vladimiro ^{[2, 3]} ; Padilha-Feltrin, Antonio ^[1]

Affiliation

^[1] Sao Paulo State Univ, UNESP, Dept Elect Engn, BR-15385000 Ilha Solteira, SP - Brazil

^[2] INESCPorto, USE Power Syst Unit, P-4200465 Oporto - Portugal

^[3] Univ Porto, FEUP, Fac Engn, P-4200465 Oporto - Portugal

• Document type: Journal article
• Source: Electric Power Systems Research; v. 89, p. 100-108, 2012.
• Web of Science Citations: 32

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. (C) 2012 Elsevier BM. All rights reserved. (AU)