Research of Distributed Parallel Immune Genetic Algorithm in Reactive Power Optimization

摘要：

A distributed parallel immune genetic algorithm (DPIGA) based on PC cluster was proposed, aiming at the disadvantage of traditional genetic algorithm, such as the bad searching quality and long computation time. It adopts the improved immune genetic algorithm (IIGA) and distributed parallel technique MPI, to implement the distributed computing on PC cluster. The integration of fuzzy logic and simulated annealing algorithm into genetic immune algorithm is presented in IIGA. The DPIGA uses the individual migration strategy to collaboratively optimize every process. The dynamic demes are adopted to balance the CPU load. Computing efficiency is introduced to judge the computing load state. An IEEE 14 test system in power system is tested. The results reveal that the algorithm has a good stable searching capacity and good parallel efficiency. Hence the proposed method should have a better future in the application.

关键词： Genetic algorithm Reactive power optimization Decimal integer encoding Parallel immune genetic algorithm

作者: Yongmei Liu Keyan Liu Wanxing Sheng

作者单位: CEPRI, District Haidian, 100085, Beijing, China Beihang University, District Haidian, 100083, Beijing, China

会议类型: 国际会议

会议名称: The Second International Symposium on Intelligence Computation and Applications(ISICA 2007)(第二届智能计算及其应用国际会议)

会议地点: 武汉

会议语种:英文

在线出版日期: 2007-09-21（万方平台首次上网日期，不代表论文的发表时间）