计及可用输电能力的风电并网系统中STATCOM的双层优化配置  

Bi-level Optimal Configuration of STATCOM in Wind Power Grid-connected System Considering Available Transfer Capacity

作　　者：陶然 张涛[1,2] 冉华军[1] 刘伉[1] 王清川 黄明娟 TAO Ran;ZHANG Tao;RAN Huajun;LIU Kang;WANG Qingchuan;HUANG Mingjuan(School of Electrical Engineering and New Energy,China Three Gorges University,Yichang 443002,China;Hubei Provincial Engineering Research Center of Intelligent Energy Technology,China Three Gorges University,Yichang 443002,China)

机构地区：[1]三峡大学电气与新能源学院,湖北宜昌443002 [2]智慧能源技术湖北省工程研究中心(三峡大学),湖北宜昌443002

出　　处：《智慧电力》2022年第12期86-93,共8页Smart Power

基　　金：国家自然科学基金资助项目(52007103)。

摘　　要：针对静止同步补偿器最佳安装位置与容量问题,建立了风电并网系统中计及可用输电能力、静态电压稳定性与投资成本的静止同步补偿器双层优化配置模型。基于后向削减法对风电出力进行场景划分,上层为多目标优化配置层,下层为最优潮流计算层;通过对多目标灰狼算法添加混沌初始化,引入粒子群算法中的速度计算方式等提出基于网格法的多目标灰狼粒子群算法以求解多目标优化问题。在IEEE 30节点上对建立模型进行计算,验证了所提模型的可行性和算法改进的有效性。Targeting the problem of optimal location and capacity of static synchronous compensator(STATCOM),the paper establishes a bi-level optimization configuration model of STATCOM in wind power integrated system considering the available transfer capacity,static voltage stability and investment cost. The scenario division of wind power output is done based on backward reduction method. The upper layer is a multi-objective optimal allocation layer,and the lower layer is a optimal power flow calculation layer. By adding the chaos initialization to the multi-objective gray wolf algorithm and introducing the speed calculation method of a particle swarm optimization algorithm,a multi-objective gray wolf particle swarm optimization algorithm based on the grid method is proposed to solve the multi-objective optimization problem. The feasibility of the model and the effectiveness of the algorithm improvement are verified by solving the model in an IEEE 30-node system.

关 键 词：静止同步补偿器 风电并网系统 可用输电能力 双层优化 多目标灰狼粒子群算法 

分 类 号：TM744[电气工程—电力系统及自动化]