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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
【摘要】 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。
【Abstract】 To improve the accuracy and efficiency and avoid premature of particle swarm optimization(PSO),an algorithm of breeding-based PSO(BBPSO) is proposed.By integrating the Breeding and PSO techniques,the algorithm has a dual group search mechanism that eliminates the shortcomings of PSO and improves population diversity,and application to cascade hydropower stations shows a better efficiency and accuracy.
【关键词】 水电工程;
粒子群优化算法;
育种算法;
梯级电站发电最优调度;
【Key words】 evolutionary computation; particle swarm optimization; breeding algorithm; optimization of cascade hydropower stations;
【Key words】 evolutionary computation; particle swarm optimization; breeding algorithm; optimization of cascade hydropower stations;
【基金】 国家自然科学基金重点项目(50539140);国家自然科学基金项目(50679098)
- 【文献出处】 水力发电学报 ,Journal of Hydroelectric Engineering , 编辑部邮箱 ,2010年01期
- 【分类号】TV737
- 【被引频次】12
- 【下载频次】343