@inproceedings{060881c0f435459da9409c451694fd87,
title = "Multiobjective particle swarm optimization for optimal power flow problem",
abstract = "A novel approach to multiobjective particle swarm optimization (MOPSO) technique for solving optimal power flow (OPF) problem is proposed in this paper. The new MOPSO technique evolves a multiobjective version of PSO by proposing redefinition of global best and local best individuals in multiobjective optimization domain. A clustering algorithm to manage the size of the Pareto-optimal set is imposed. The proposed MOPSO technique has been implemented to solve the OPF problem with competing and non-commensurable cost and voltage stability enhancement objectives. The optimization runs of the proposed approach have been carried out on a standard test system. The results demonstrate the capabilities of the proposed MOPSO technique to generate a set of well-distributed Pareto-optimal solutions in one single run.",
keywords = "Multiobjective optimization, Optimal power flow, Particle swarm optimization",
author = "Abido, {M. A.}",
year = "2008",
doi = "10.1109/MEPCON.2008.4562380",
language = "English",
isbn = "1424419336",
series = "2008 12th International Middle East Power System Conference, MEPCON 2008",
pages = "392--396",
booktitle = "2008 12th International Middle East Power System Conference, MEPCON 2008",
}