基于云自适应遗传算法的机组负荷分配  

Application of Improved Cloud Adaptive Genetic Algorithm in Thermal Power Units Load Distribution

作　　者：申哲巍[1] 张树芳 孙东海[1] 

机构地区：[1]华北电力大学能源动力与机械工程学院,河北保定071003

出　　处：《电力科学与工程》2013年第3期51-54,共4页Electric Power Science and Engineering

摘　　要：将云自适应遗传算法应用于机组负荷优化分配,并根据负荷分配的具体要求对遗传参数的设置进行了改进。算法不仅继承自适应遗传算法计算速度快的优点,而且由于云模型既有随机性又同时具有稳定倾向性,避免了较优个体遗传概率为零的弊端,因此不易陷入早熟,鲁棒性更高,应用于机组负荷分配能够得到理想的效果。Applied cloud adaptive genetic algorithm into units load dispatch problem, and improved the genetic parameters according to the specific requirements of the load distribution by the authors. The algorithm not only inher- ites the advantages of adaptive genetic algorithm that calculating rapidly, but also avoides the drawbacks that the genetic probability of better individual is zero for cloud model has the properties of stable tendency as well as randomness. So the algorithm is uneasy to precocious and has higher robust, it could be able to get ideal effect for solving the units load dispatch problem.

关 键 词：负荷分配 遗传算法 云模型 自适应 

分 类 号：TK212.4[动力工程及工程热物理—动力机械及工程]