改进GA算法的电力系统机组优化组合研究  

Improved Genetic Algorithm and Its Study in Unit Commitment Optimization

作　　者：蒋秀洁[1] 黄景光[1] 袁兆强[1] 马小强[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1期32-36,共5页Journal of China Three Gorges University：Natural Sciences

摘　　要：提出了一种新的基于实数和二进制数统一编码的改进遗传算法.把机组组合问题分解为两个优化子问题,分别对其优化.应用实数编码来模拟功率并用实数遗传算法解决负荷经济分配问题,同时结合二进制编码模拟机组启停状态,解决了机组优化组合的0-1混合整数非线性规划问题.本算法运用到模拟10台机组的优化组合研究中,取得了很好的效果.A new genetic algorithm based on the real-coding and binary coding is put forward. It effectively uses the real-coded genetic algorithm＇s perfect advantage to solve the power problem and the binary-coded genetic algorithm＇s simulating advantage to slovc the unit commitment up/down problem. This algorithm has successfully solved unit commitment problem and has gained an commitment system study. excellent results through the experiments in 10 units

关 键 词：实数编码 二进制编码 改进遗传算法 机组优化组合 

分 类 号：TK018[动力工程及工程热物理]