基于E-C-K-均值聚类和SOP优化的分布式电源双层规划

BI-LEVEL DISTRIBUTED POWER PLANNING BASED ON E-C-K-MEANS CLUSTERING AND SOP OPTIMIZATION

在含智能软开关(SOP)的配电网中针对分布式电源(DG)提出一种双层优化配置模型。上层以运营商年收益最大为目标求解DG安装的位置和容量,下层通过对SOP进行约束使网络运行性能最优,考虑到负荷和分布式电源输出的时间序列特征,设计一种新的E-C-K-means聚类算法对四季场景下的风速和辐照度进行聚类,得到典型场景日曲线。考虑到规划问题属于大规模混合整数非线性的问题,需要将离散变量与连续变量进行解耦,采用遗传算法和原对偶内点法混合算法进行求解;最后基于改进的IEEE33节点配电网系统,对优化模型和求解方法的有效性进行验证分析。

A bi-level optimized configuration model of distributed generations is proposed in distribution networks with soft open point(SOP). The upper-level solves the installation location and capacity with the goal of maximizing the operator’s annual revenue. The lower-level optimizes the network operation performance by constraining the SOP. Considering the time series characteristics of the load and distributed power output,a new clustering algorithm is designed to cluster the wind speed and irradiance in four season scenes to obtain the daily curve of typical scenes. Since the distributed power planning problem is a large-scale mixed integer non-linear problem,it is necessary to decouple the discrete variables from the continuous variables. Therefore,a hybrid algorithm of genetic algorithm and original dual interior point method is used to solve the problem. Finally,based on the improved IEEE33 node distribution network system,the validity of the optimization model and the solution method are verified and analyzed.