丘文千
QIU Wen-qian

• 1:浙江省电力设计院

摘要(Abstract)：

利用遗传算法和传统优化方法的互补特性,采用混合优化方法求解包含离散和连续变量的无功优化问题。遗传算法的选择、交叉和变异操作仅作用于离散变量,对种群进行全局广度搜索,运用传统优化方法对种群个体中的连续变量进行优化使其移动到局部最优点上。为保证对连续变量的优化效果,选择了基于函数变换与广义逆的优化新算法。混合优化算法模型简单规范,遗传算法擅长处理离散变量和传统优化方法速度快、数值稳定性好的优势得到发扬。算法实用性和有效性通过算例及工程应用得到验证。
Hybrid optimization methods are used to resolve reactive power optimization with discrete and continuous variables,by which the complementary characteristics of genetic and traditional optimization algorithms are utilized.Genetic operations(such as selection,crossover and mutation)are acted on discrete variables only.The genetic algorithms are used to make the global searches to the population.Before a new offspring is selected into the population,it must move to the local optimal point by using the traditional optimization methods to the continuous variables.To ensure the effects of the local optimization,a new optimization algorithm which is based on function transform and generalized inverse of matrices is used.The model of hybrid optimization algorithm is simplified and normal,which has the advantage of genetic algorithms which treated discrete variables conveniently and traditional optimization methods which calculated fast and steady.The practicability and effectiveness of algorithms are proved by case studies.

关键词(KeyWords)： 电力系统;分析;无功优化;广义逆矩阵;遗传算法
electric power system;analysis;reactive power optimization;generalized inverse of matrices;genetic algorithms

Abstract:

Keywords:

基金项目(Foundation):

作者(Author): 丘文千
QIU Wen-qian

DOI: 10.19585/j.zjdl.2008.04.001

参考文献(References)：

• [1]许诺,黄民翔.原对偶内点法与定界法在无功优化中的应用[J].电力系统及其自动化学报,2000,12(3):26-30.
• [2]赵晋泉,候志俭,吴际舜.牛顿最优潮流算法中离散控制量的新处理方法[J].电力系统自动化,1999,23(23):37-40.
• [3]黄伟,刘明波.混合整数无功优化问题的连续优化方法[J].继电器,2005,33(11):5-8.
• [4]谭涛亮,张尧.基于禁忌遗传混合算法的电力系统无功优化[J].电网技术,2004,28(11):57-61.
• [5]熊信银,吴耀武.遗传算法及其在电力系统中的应用[M].武汉:华中科技大学出版社,2002.
• [6]丘文千.具有变量范围约束的潮流算法在OPF中的应用[J].电力系统自动化,2007,31(15):35-40.
• [7]丘文千.电力系统无功规划的综合优化[J].浙江电力,2008,27(3):1-5.
• [8]王锡凡.电力系统优化规划[M].北京:水利电力出版社,1990.