A Chaos Particle Swarm Optimization Algorithm for Optimal Power Flow

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The chaos particle swarm optimization algorithm was presented to solving optimal power flow. The proposed OPF considers the total cost of generators as the objective functions. To enhance the performance of algorithm, a premature convergence strategy was proposed. The strategy can be divided into two parts. In the first part, a method is introduced to judge premature convergence, while another part provides an advance method to improve the performance of algorithm with searching the solution in total feasible region. The control strategy used to prevent premature convergence will obtain starting values for initial particle before program iterating, so it can provide bitter probability of detecting global optimum solution. The simulation results on standard IEEE 30-bus system minimizing fuel cost of generator show the effectiveness of the chaos particle swarm optimization algorithm, and can obtain a good solution.

Info:

Periodical:

Advanced Materials Research (Volumes 1008-1009)

Edited by:

Hongbo Fan, Xiaoguo Liu and Shengzhou Chen

Pages:

466-472

DOI:

10.4028/www.scientific.net/AMR.1008-1009.466

Citation:

C. J. Xia et al., "A Chaos Particle Swarm Optimization Algorithm for Optimal Power Flow", Advanced Materials Research, Vols. 1008-1009, pp. 466-472, 2014

Online since:

August 2014

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Price:

$38.00

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