Title: Distributed optimal power flow using bacterial swarming algorithm

Authors: Q.H. Wu, T.Y. Ji, M.S. Li, Z. Lu

Addresses: Electrical Engineering and Electronics, The University of Liverpool, Liverpool, L69 3GJ, UK. ' Electrical Engineering and Electronics, The University of Liverpool, Liverpool, L69 3GJ, UK. ' Electrical Engineering and Electronics, The University of Liverpool, Liverpool, L69 3GJ, UK. ' Electrical Engineering and Electronics, The University of Liverpool, Liverpool, L69 3GJ, UK

Abstract: With the increasing use of distributed intelligent devices and the demand of separated power network managing, distributed control of a complex power system becomes more and more important in application. In a distributed power flow optimisation, the cost of the network can be optimised by coordinating the control of generators and taps in a subarea partition. In this paper, a bacterial swarming algorithm (BSA) is presented to solve an optimisation problem of distributed power flow. BSA is designed from a searching framework that combines the underlying mechanisms of bacterial chemotaxis and quorum sensing. The algorithm has been evaluated by simulation studies, which were undertaken on an IEEE 118-bus test system, in comparison with a genetic algorithm (GA) and a particle swarm optimiser (PSO).

Keywords: distributed power flow; optimal power flow; bacterial swarming algorithm; BSA; optimisation; power systems; bacterial chemotaxis; quorum sensing; particle swarm optimisation; PSO.

DOI: 10.1504/IJMIC.2010.033216

International Journal of Modelling, Identification and Control, 2010 Vol.9 No.4, pp.409 - 416

Published online: 13 May 2010 *

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