Particle swarm optimization with Exponentially Varying Inertia Weight Factor for solving Multi-Area Economic Dispatch problem

Rani Chinnappa Naidu, Emil Petkov, Krishna Busawon, Mohamed Farrag

Research output: Contribution to conferencePaper

4 Citations (Scopus)

Abstract

This paper aimed at exploring the performance of Particle Swarm Optimisation with Exponentially Varying Inertia Weight Factor (PSO-EVIWF) for solving Multi-Area Economic Dispatch (MAED) problem with tie line constraints considering valve-point loading in each area. The effectiveness of the proposed algorithm has been verified on 4 interconnected areas with 16 generators standard test system. The paper presents the search capability and convergence behavior of the proposed method. Simulation results show that the PSO-EVIWF achieved quality solutions and smooth convergence characteristics and it is an alternative method for solving MAED problem.
Original languageEnglish
DOIs
Publication statusPublished - Nov 2014
EventEFEA 2014: 3rd International Symposium on Environmental Friendly Energies and Applications - Paris, France
Duration: 1 Nov 2014 → …

Conference

ConferenceEFEA 2014: 3rd International Symposium on Environmental Friendly Energies and Applications
Period1/11/14 → …

Keywords

  • Economic dispatch
  • Multi area economic dispatch
  • particle swarm optimisation
  • exponentially varying inertia weight factor

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