改进二进制粒子群算法在配电网重构中的应用

The application of improved binary particle swarm optimization in distribution network reconfiguration

将混合蛙跳思想引入粒子群算法,并结合遗传算法中的选择交叉操作,提出一种改进二进制粒子群算法,来解决配电网重构中的问题。并且动态调整粒子速度更新公式中的惯性系数,使粒子能够随更新次数的变化动态改变全局和局部搜索能力,防止算法早熟,以找到全局最优解。文章最后对典型IEEE33节点算例进行仿真,并与遗传算法进行对比分析,结果表明该方法不仅能有效避免算法早熟、快速收敛,而且稳定性好。

This paper applies the idea of mixing leapfrog particle swarm algorithm and selection crossover operation of genetic algorithm to particle swarm algorithm,and puts forward an improved binary particle swarm optimization to solve the problem of distribution network reconfiguration. Through dynamically adjusting the inertia coefficient of particle swarm speed optimization formula,so that the particles can dynamically change the global and local search capability with the number of updates in order to prevent the algorithm from premature and find the optimal solution. Finally,the example of typical IEEE33 node is simulated and compared with genetic algorithm,the simulation results illustrate that this method can avoid the algorithm premature effectively with the advantages of rapid convergence and good stability.