改进云遗传算法在负荷优化分配中的应用  

Application of Improved Cloud 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]华北电力大学动力工程系,河北保定071003

出　　处：《陕西电力》2012年第12期43-46,共4页Shanxi Electric Power

摘　　要：改进了一种基于云模型的遗传算法用以解决火电机组负荷优化分配问题。该算法将遗传算法的重组算子及变异算子进行云化,继承了云模型的随机性和稳定倾向性的特点。将该方法应用于某厂4台机组进行负荷优化分配,并与标准遗传算法进行比较,结果显示该方法的可行解优于标准遗传算法,证明了该方法在求解机组负荷优化分配问题的有效性及优越性。The paper improves a genetic algorithm based on cloud model for solving thermal power units load dispatch problem. The algorithm transforms the recombination operator and mutation operator into cloud-based operators, and carries forward the advantage of the cloud model which has the properties of randomness and stable tendency. The new algorithm is applied to the load distribution problem for four units in a certain power plant, the result is obviously better than the standard genetic algorithm when comparing and shows that the new algorithm is feasible in solving the thermal power units load distribution problem.

关 键 词：负荷分配 遗传算法 云模型 火电机组 

分 类 号：TK212.4[动力工程及工程热物理—动力机械及工程]