摘要
针对电力系统经济负荷分配问题的特点,应用极大熵理论将经济负荷分配问题转化为可微问题·在分析了遗传算法与传统数学优化方法的不同优势与特性的基础上,将遗传算法与传统数学优化方法相结合引入局部搜索算子实现快速搜索,提出了一种求解电力系统经济负荷分配问题的改进遗传算法·同时,应用多点均匀交叉算子提高遗传算法的全局收敛性能,将种群逐步向最优点进行引导·实例研究结果验证了方法的有效性·
The economic dispatch problem （EDP） of power systems is approximated and converted into a differentiable one by way of maximum entropy in accordance to its characteristics. The different advantages and characteristics of conventional optimization metheds and genetic algorithm are analyzed, then they are integrated together with a local searching operator introduced into implement rapid searching. An improved genetic algorithm is thus presented to solve EDP of power systems, of which the ,searching speed and local searching capability are improved by BFGS operator. At the same time, the uniform multiple individuals crossover operator is applied to improve global convergence and lead the population to the global optimum. Two examples are given to verify the validity of the algorithm.
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2006年第11期1181-1184,共4页
Journal of Northeastern University(Natural Science)
基金
国家自然科学基金资助项目(60374003)
国家重点基础研究发展规划项目(2002CB312200).
关键词
电力系统
经济负荷分配
极大熵
遗传算法
局部搜索算子
多点均匀交叉算子
power system
economic dispatch（ED）
maximum entropy
genetic algorithm
local .searching operator
uniformmultiple individuals crossover operator
