混合遗传算法在电厂机组负荷分配中的应用  

Application of Hybrid Genetic Algorithm to Load Allocation Among Power Generating Units

作　　者：黄文华[1] 王仁明[1] 刘芬[1] 

机构地区：[1]三峡大学电气信息学院,湖北宜昌443002

出　　处：《三峡大学学报（自然科学版）》2006年第5期400-403,共4页Journal of China Three Gorges University：Natural Sciences

摘　　要：机组负荷优化分配是一种可提高电厂经济性的手段,越来越成为一个令人有兴趣的研究课题,但目前还没有得到一种绝对严格的算法.引入模糊理论建立了电站机组负荷分配模型,并运用混合遗传算法求解,该算法不同于常规优化算法特点在于:容易得到全局最优解,有较强的鲁棒性,适合大规模的复杂系统求解.最后给出了一个具体的例子来阐述方法的有效性.The optimization of load allocation among power generating sets is a measure for improving economy of power plants; and it is becoming a more interesting studying topic; but now there is no absolutely strict algorithm. In this paper, a model of optimization of load allocation among power generating sets is established with fuzzy theory; and applied the hybrid genetic algorithm to solve the model. The algorithm is different from normal optimization algorithms as follows： easier getting best solutions in full place; having better robust; and being suitable for solving the complicated systems with large-scale. Finally, an example is given to illustrate the validity of the approach.

关 键 词：电力系统 机组组合 隶属函数 遗传算法 

分 类 号：TM715[电气工程—电力系统及自动化]