Bacterial Foraging Algorithm with Varying Population for Optimal Power Flow

Authors:
M. S. Li;W. J. Tang;W. H. Tang;Q. H. Wu;J. R. Saunders
Affiliations:
Department of Electrical Engineering and Electronics,;Department of Electrical Engineering and Electronics,;Department of Electrical Engineering and Electronics,;Department of Electrical Engineering and Electronics,;School of Biological Sciences, The University of Liverpool, Liverpool L69 3GJ, U.K.
Venue:
Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing
Year:
2009

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Abstract

This paper proposes a novel optimization algorithm, Bacterial Foraging Algorithm with Varying Population (BFAVP), to solve Optimal Power Flow (OPF) problems. Most of the conventional Evolutionary Algorithms (EAs) are based on fixed population evaluation, which does not achieve the full potential of effective search. In this paper, a varying population algorithm is developed from the study of bacterial foraging behavior. This algorithm, for the first time, explores the underlying mechanisms of bacterial chemotaxis, quorum sensing and proliferation, etc., which have been successfully merged into the varying-population frame. The BFAVP algorithm has been applied to the OPF problem and it has been evaluated by simulation studies, which were undertaken on an IEEE 30-bus test system, in comparison with a Particle Swarm Optimizer (PSO) [1].