育种粒子群算法在梯级水电站优化调度中的应用

Application of BBPSO to optimal operation of cascade hydropower stations

为了提高粒子群优化(Particle Swarm Optimization,PSO)算法的计算精度和计算效率,避免"早熟",提出了育种粒子群优化算法(Breeding-based Particle Swarm Optimization,BBPSO)。该算法模型将育种算法和PSO算法有机结合,构建双群体搜索机制,既利用PSO算法的快速演化能力,又利用育种算法模型中的繁殖操作增加群体多样性。将该算法模型应用于梯级水电站发电最优调度中,仿真结果表明,和标准PSO算法相比,BBPSO具有更好的全局寻优能力和较快的收敛速度,能有效应用于梯级电站发电联合优化调度中。

To improve the accuracy and efficiency and avoid premature of patti an algorithm of breeding-based PSO（BBPSO） is proposed. By integrating the the algorithm has a population diversity, dual group search and application to mechanism that eliminates the short cascade hydropower stations shows a b cle swarm optimization （PSO） , Breeding and PSO techniques, comings of PSO and improves etter efficiency and accuracy.