JOURNAL OF COMPUTERS (JCP)
ISSN : 1796-203X
Volume : 4    Issue : 9    Date : September 2009

Distribution Network Reconfiguration Based on Particle Clonal Genetic Algorithm
Yemei Qin and Ji Wang
Page(s): 813-820
Full Text:
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Abstract
Distribution network reconfiguration is an important aspect of automation and optimization of
distribution network system. To handle massive binary code infeasible solutions in distribution
network reconfiguration, a kind of sequence code is presented in which a loop is a gene and the
label of each switch in the loop is the gene value. To solve mutation probability and slow the
convergence of clonal genetic algorithm (CGA) in the later stage, in this paper particle clonal genetic
algorithm (PCGA) is proposed, in which we build particle swarm algorithm (PSO) mutation operator.
PCGA avoids the premature convergence of PSO and the blindness of CGA. It ensures evolution
direction and range based on historical records and swarm records. The global optimal solution
can be obtained with fewer generations and shorter searching time. Compared with CGA and clonal
genetic simulated annealing algorithm (CGSA), IEEE33 and IEEE69 examples show that PCGA can
cut the calculation time and promote the search efficiency obviously.

Index Terms
sequence code, distribution network reconfiguration, infeasible solution, PCGA