自适应变异粒子群算法及在输电网规划中的应用

Particle Swarm Optimization Algorithm with Adaptive Mutation and Its Application in Power Transmission Network Planning

针对标准粒子群优化(SPSO)算法易陷入局部最优的缺点,引入了一种自适应变异的粒子群优化(AMPSO)算法,并应用于电力系统输电网规划。该算法在迭代过程中加入变异操作,并根据种群适应度方差值自适应地调整变异概率的大小,以此来增强算法跳出局部最优的能力。在输电网规划算例中的应用结果表明,变异操作改善了算法的寻优性能,使得AMPSO算法的寻优效率远高于SPSO算法。

Aiming at the deficiency of standard particle swarm optimization （SPSO） algorithm, i. e., easily plunging into the local optimum, an adaptive mutation particle swarm optimization （AMPSO） algorithm is applied to the power transmission network planning. The algorithm adds mutation operation in iteration process to enhance its ability to break away from local optimum, and the mutation probability is adaptively adjusted by variance of the population＇s fitness. Numerical simulation results of power transmission network planning demonstrate that the optimum searching performance of AMPSO is improved by mutation operation, so the searching efficiency of AMPSO algorithm is far better than that of SPSO algorithm.