@inproceedings{0f1282503f85465d917a031afcd0bec4,
title = "Multiobjective optimal power flow using strength pareto evolutionary algorithm",
abstract = "In this paper, a novel multiobjective evolutionary algorithm for optimal power flow (OPF) problem is presented. The OPF problem is formulated as a nonlinear constrained multiobjective optimization problem where the fuel cost and the voltage stability index are to be minimized simultaneously. A new Strength Pareto Evolutionary Algorithm (SPEA) based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and non-commensurable objectives. A hierarchical clustering algorithm is imposed to provide the decision maker with a representative and manageable Pareto-optimal set. The results demonstrate the capabilities of the proposed approach to generate true and well-distributed Pareto-optimal nondominated solutions in one single run. The results also show the superiority of the proposed approach and confirm its potential to solve the multiobjective OPF problem.",
keywords = "Evolutionary algorithms, Multiobjective optimization, Optimal power flow",
author = "Abido, \{M. A.\}",
year = "2004",
language = "English",
isbn = "1860433650",
series = "39th International Universities Power Engineering Conference, UPEC 2004 - Conference Proceedings",
pages = "457--461",
booktitle = "39th International Universities Power Engineering Conference, UPEC 2004 - Conference Proceedings",
}