改进遗传算法的无功优化规划在伊盟电网中的实现

An Improved Genetic Algorithm for Reactive Power Planning of Yimeng Power System

电力系统无功优化规划是一个较复杂、多目标、非线性的混合规划。用常规的线性和非线性等方法进行优化计算 ,存在离散变量的近似处理问题 ,不符合无功规划的实际。而遗传算法由于自身特点 ,特别适合于解决多目标混合优化方面的问题 ,具有稳定的收敛特性 ,是一种先进的全局优化方法。其不足之处在于计算时间长 ,在种群和遗传代数不是足够大的情况下 ,易于收敛于局部极值点。为此提出了改进遗传算法 。

The reactive power optimal planning of power system is a complicated nonlinear mixed planning problem with multi-objectives. The optimizing computation using conventional linear and nonlinear methods has a disadvantage, i.e. the dispersed variable approximation, which makes it can't correspond to the reality of reactive power planning. On the contrast, the genetic algorithm particularly suits for the mixed optimization problem with multi-objectives. The genetic algorithm has stable convergence, and is an advanced global optimization method. The shortcoming of the genetic algorithm is the longer computation time. And if not given sufficient population and genetic generation, this algorithm tends to converge to local extreme value point. Therefore, this paper presents a modified genetic algorithm, which has advantages of higher computation speed and computation accuracy over the traditional genetic algorithm.