Multi-objective differential evolution for optimal power flow

M. A. Abido, N. A. Al-Ali

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

52 Scopus citations

Abstract

This paper presents a multiobjective differential evolution (MODE) based approach to solve the optimal power flow (OFF) problem. OFF problem has been treated as a true multiobjective constrained optimization problem. Different objective functions and different operational constraints have been considered in the problem formulation. A clustering algorithm is applied to manage the size of the Pareto set. Also, an algorithm based on fuzzy set theory is used to extract the best compromise solution. Simulation results on IEEE-30 bus test system show the effectiveness of the proposed approach in solving true multi-objective OFF and also finding well distributed Pareto solutions.

Original languageEnglish
Title of host publicationPOWERENG 2009 - 2nd International Conference on Power Engineering, Energy and Electrical Drives Proceedings
Pages101-106
Number of pages6
DOIs
StatePublished - 2009

Publication series

NamePOWERENG 2009 - 2nd International Conference on Power Engineering, Energy and Electrical Drives Proceedings

Keywords

  • Differential evolution
  • Evolutionary algorithms
  • Multiobjective optimization
  • Optimal power flow

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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