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].
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Li, M.S., Tang, W.J., Tang, W.H., Wu, Q.H., Saunders, J.R. (2007). Bacterial Foraging Algorithm with Varying Population for Optimal Power Flow. In: Giacobini, M. (eds) Applications of Evolutionary Computing. EvoWorkshops 2007. Lecture Notes in Computer Science, vol 4448. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71805-5_4
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DOI: https://doi.org/10.1007/978-3-540-71805-5_4
Publisher Name: Springer, Berlin, Heidelberg
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