基于改进遗传算法的电力系统机组优化组合  

Unit Commitment of Power System Based on Improved Genetic Algorithm

作　　者：唐伟[1] 李群湛[1] 余丹[1] 林飞[1] 

机构地区：[1]西南交通大学电气工程学院,610031

出　　处：《电气应用》2006年第1期64-66,共3页Electrotechnical Application

摘　　要：用遗传算法解决电力系统机组组合及机组间的负荷分配问题。在简单遗传算法基础上,提出了将自适应遗传算法应用于机组优化组合。该算法的交叉率随种群中的最大适应度值和每代种群的平均适应度值的变化而自动改变;变异率随适应度值和进化代数的变化而自动调节。通过对算例的计算分析表明,该算法与简单遗传算法相比具有更高的精度和收敛度。How to solve unit commitment problem and load dispatch of power system by genetic algorithm is researched. A adaptive genetic algorithm, that is applied to unit commitment, is put forward on the basis of simple genetic algorithm. It applies adaptive crossover rate, which is changed with the maximum colony adaptation degree and the average colony adaptation degree of each generation. The variation rate of adaptive GA is adjusted by the colony adaptation degree and the evolutionary generation. The results of calculation example shows that the adaptive genetic algorithm is more precise and more convergent than simple genetic algorithm in the unit commitment.

关 键 词：机组组合 遗传算法 自适应 

分 类 号：TM73[电气工程—电力系统及自动化]