基于数学形态学和遗传算法的配电网动态无功优化方法

提出了一种基于数学形态学和遗传算法的配电网动态无功优化方法，通过构造数学形态学滤波器对由染色体的等位基因构成的二值图像进行滤波，将对补偿调压设备动作次数的处理问题转化为离散二值图像的滤波问题。为提高遗传算法的计算速度，对交叉和变异操作进行了改进：基于遗传性状的思想，防止了交叉操作中对优良基因组合的破坏；借鉴粒子群算法中根据个体极值和全局极值修正个体速度和位置的思想，提出了根据基因性状进行进化变异的方法。分别采用改进遗传算法、简单遗传算法和该动态无功优化方法对某区域配电系统进行无功优化，结果验证了该优化方法的正确性和有效性。

A Mathematical Morphology and Genetic Algorithm Based Dynamic Reactive Power Optimization Method for Distribution Network

A mathematical morphology and genetic algorithm based dynamic reactive power optimization method for distribution network is proposed.By means of constructing mathematical morphology filter,the binary image composed by allelic genes of chromosome is filtered and the problem that deals with the action times of voltage regulating devices for compensation is turned into filtering problem of discrete binary image.To quicken the calculation speed of genetic algorithm,the chiasma operation and mutation operation are improved;based on the thinking of inheritable character,the destruction of fine gene combination during chiasma operation is prevented;drawing lessons from the thinking of modifying individual speed and position in the light of individual extremum and global extremum in particle swarm optimization(PSO) algorithm,an evolutional mutation method based on gene character is put forward.Taking the reactive power optimization of a regional distribution network for example,the reactive power optimization is carried out by improved genetic algorithm,simple genetic algorithm and the proposed dynamic reactive power optimization respectively,optimization results show that the proposed dynamic reactive power optimization method is efficient and correct.