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
dc.contributor.author | Renan Maciel | en |
dc.contributor.author | Vladimiro Miranda | en |
dc.contributor.author | Mauro Rosa | en |
dc.contributor.author | Antonio Padilha-Feltrin | en |
dc.date.accessioned | 2017-11-17T11:57:34Z | |
dc.date.available | 2017-11-17T11:57:34Z | |
dc.date.issued | 2012 | en |
dc.description.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. | en |
dc.identifier.uri | http://repositorio.inesctec.pt/handle/123456789/3318 | |
dc.language | eng | en |
dc.relation | 4660 | en |
dc.relation | 208 | en |
dc.rights | info:eu-repo/semantics/openAccess | en |
dc.title | Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation | en |
dc.type | article | en |
dc.type | Publication | en |