摘要
将粒子群算法和混沌算法相结合,用于求解水库中长期优化调度问题。它利用了粒子群优化算法收敛速度快和混沌运动遍历性、随机性等特点,对传统粒子群算法进行改进,摆脱了粒子群算法后期易陷入局部极值点的缺点,同时又保持了前期搜索的快速性。通过实例计算,结果表明该算法在收敛性和稳定性等方面明显优于传统粒子群优化算法,是一种有效的搜索算法。
This paper proposes a mixed algorithm based on the chaos-optimization algorithm and the particle swarm optimization algorithm to optimize the mid-long-term reservoir operation. The proposed algorithm improves the convergence by taking advantages of the two traditional algorithms, and can avoid the shortcoming of being easily trapped in a local extremum at the later evolution stage while maintain a rapid rate at the initial stage. Test cases indicate a better performance of the new algorithm than PSO in terms of convergence and stability.
出处
《水力发电学报》
EI
CSCD
北大核心
2010年第1期102-105,共4页
Journal of Hydroelectric Engineering
基金
国家自然科学基金项目(50539140)
国家自然科学基金项目(50679098)
关键词
水电站
中长期优化调度
粒子群算法
混沌搜索
hydropower station
mid-long term optimal operation
particle swarm optimization algorithm
chaos search
