基于点估计法的分布式电源的配置优化

Optimal Allocation of Distributed Generation Based on Point Estimate Method

文中主要研究在考虑风光火电入网的不确定性因素引入概率潮流,以配电网年综合费用最小为目标函数,采用内嵌三点估计法的遗传算法求解最佳分布式电源的配置方案。在IEEE33节点系统算例中,考虑几种方案下基于蒙特卡洛的遗传算法(GA-MCS)与基于点估计法的遗传算法(GA-PEM)进行比较。算例结果表明,两种方法得出几乎相同的结果,但基于三点估计法的遗传算法计算量小,速度快七倍。

The scope of this study is considering uncertainties of a power distribution network with the wind,photovoltaics and the fuel generation,the probability flow is introduced.Based on the minimum comprehensive cost of distribution network as the objective function,the genetic algorithm with embedded three point estimation method is used to solve the optimal distributed power allocation scheme.In the case of IEEE33 node system,the genetic algorithm(GA-MCS)based on Monte Carlo method and the genetic algorithm(GA-PEM)based on the point estimation method are compared in several schemes.Example results show that the two methods can get almost the same results,but GA with embedded the three points estimation method is small,and the speed is seven times faster.