应用于电力系统无功规划的一种新算法

电力系统无功优化规划属于非线性混合优化问题，其控制变量既有连续变量又有离散变量，如果不能实现离散变量的精确处理，将导致优化结果不符合电力系统的实际．遗传算法是解决多目标混合优化问题的全局优化算法，但是具有优化时间长，易于收敛于局部极值点等不足，为此提出了灾变遗传算法，可以显著提高无功优化规划的计算速度和搜索精度，优化结果比传统遗传算法更优．

New Algorithm of VAR Compensation Applied in Power System

The VAR compensation of power system is a complicated nonlinear mixed planning problem with multi-objectives. The operation variables include both continuous variables and discrete variables. The dispersed variable approximation, which makes it can＇t correspond to the reality of power system. The genetic algorithm （GA） particularly suits for the mixed optimization problem with multi-objectives. The shortcoming of the genetic algorithm is the longer computation time. And ff not given sufficient population and genetic generation, this algorithm tends to converge to local extreme value point. According to this, it presented a modified cataclysmic GA principle. It has advantages of high computation speed and computation accuracy over the traditional genetic algorithm.