Distributed optimal power flow using bacterial swarming algorithm. (14th May 2010)

• Record Type: Journal Article
• Authors: Wu, Q.H.; Ji, T.Y.; Li, M.S.; Lu, Z.
• Is Part Of: International journal of modelling, identification and control. Volume 9:Number 4(2010)
• Page Start: 409
• Page End: 416
• Publication Date: 2010-05-14
• Subjects: distributed power flow -- optimal power flow -- bacterial swarming algorithm -- BSA -- optimisation -- power systems -- bacterial chemotaxis -- quorum sensing -- particle swarm optimisation -- PSO; Engineering -- Methodology -- Periodicals; Science -- Methodology -- Periodicals; 001.42
• Languages: English
• ISSNs: 1746-6172

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).