基于改进的无尺度网络的高斯动态粒子群优化算法在舰船电网故障重构中的应用  

Application of Gaussian dynamic particle swarm optimization algorithm based on improved scale-free network in fault reconfiguration of ship power system

作　　者：陈洋[1] 刘彦呈[1] 王川[1] 

机构地区：[1]大连海事大学轮机工程学院,辽宁大连116026

出　　处：《上海海事大学学报》2017年第1期79-83,共5页Journal of Shanghai Maritime University

基　　金：辽宁省自然科学基金(2014025006)

摘　　要：针对当前优化算法在处理大规模舰船电网重构问题时易陷于局部极值的缺点,提出一种基于改进的无尺度网络的高斯动态粒子群优化(Gaussian Dynamic Particle Swarm Optimization,GDPSO)算法.该算法融合无尺度网络理论与种群拓扑结构,采用改进的无尺度网络BA模型随机地逐渐增加种群拓扑规模,增加种群多样性,提高种群跳出局部极值的能力.以某20节点和扩充为60节点的舰船电网为例进行故障后重构测试.结果表明,该算法对多维度舰船电网重构有效.To overcome the shortcoming that the existing optimization algorithm is prone to a local extre-mum when dealing with large-scale reconfiguration issues of ship power system, Gaussian Dynamic Parti-cle Swarm Optimization（ GDPSO） algorithm based on the improved scale-free network is proposed. This algorithm integrates the scale-free network theory with the population topology structure. It adopts the modified BA model of scale-free network to increase the scale of population topology randomly, which can increase the population diversity and improve the ability of population jumping out of the local extremum. Fault reconstruction tests are run with the cases of a 20-node ship power system and an expanded 60-node ship power system. Results show that the proposed algorithm is effective for multi-dimensional ship power system reconfiguration.

关 键 词：舰船电网 故障重构 高斯动态粒子群优化 无尺度网络 

分 类 号：U665.12[交通运输工程—船舶及航道工程]