育种进化的改进遗传算法在水电站负荷分配中的应用  

Breed-evolutionary Improved Genetic Algorithm for Load Dispatch of Hydropower Station

作　　者：邓丽丽[1] 杨侃[1] 王启明 陈静 周佳佳[1] 

机构地区：[1]河海大学水文水资源学院,江苏南京210098 [2]句容市水利农机局,江苏镇江212400 [3]宜兴市水利农机局,江苏宜兴214207

出　　处：《水文》2015年第2期22-27,共6页Journal of China Hydrology

基　　金：国家重点基础研究发展规划973项目(2012CB417006);国家科技支撑计划课题(2009BAC56B03)

摘　　要：针对遗传算法求解水电站负荷优化分配问题时常出现的收敛性差、易早熟等问题,提出一种基于育种进化的改进遗传算法。改进算法运用部分解约束的初始种群生成法避开空蚀振动区,定义了与群体进化程度有关的种群多样性函数和种群多样性阈值,同时有效地应用了遗传的全局搜索能力和育种的局部搜索能力。以三峡水电站为例与标准遗传算法进行了比较,不同的负荷分配结果表明:育种进化的改进遗传算法能够避开空蚀振动区的影响,保证机组的稳定安全运行;同时由于育种进化的强局部搜索能力,保持了种群的多样性,提高了算法的搜索能力和收敛性。Facing on the bad convergence and easy premature often emerged in Genetic Algorithm making solution of hydropower station economic load dispatch, the Breed-evolutionary Improved Genetic Algorithm （BIGA） was proposed. BIGA used the partial solution constraint initial population generation method to avoid cavitations-vibration range, so as to describe the level of group-evolution, and define the function of population-diversity and threshold of population-diversity. Meanwhile, the global searching ability of Genetic Algorithm and local searching ability of Breed were effectively applied. A contrast between BIGA and SGA applied for the Three Gorges hydropower station was presented. The distribution results based on several loads show that： In BIGA, stable and safe operation of unit were ensured by avoiding cavitations-vibration range. And, with the strong local searching ability of breed, the population diversity was maintained, and the searching ability and convergence of the algorithm were improved.

关 键 词：厂内经济运行 负荷优化分配 遗传算法 育种 部分解约束 

分 类 号：TV697.1[水利工程—水利水电工程]