基于改进灰狼优化算法的含光伏配电网动态无功优化  

Dynamic reactive power optimization of photovoltaic distribution network based on improved gray wolf optimization algorithm

作　　者：于惠钧[1] 马凡烁 陈刚[1] 杨驰泽 李嘉轩 YU Huijun;MA Fanshuo;CHEN Gang;YANG Chize;LI Jiaxuan(College of Electrical and Information Engineering,Hu’nan University of Technology,Zhuzhou,Hu’nan 412007)

机构地区：[1]湖南工业大学电气与信息工程学院,湖南株洲412007

出　　处：《电气技术》2024年第4期7-15,58,共10页Electrical Engineering

基　　金：湖南省教育厅科学研究项目(20A162);湖南省自然科学基金项目(2021JJ50052)。

摘　　要：针对光伏并网对配电网造成的电压波动、线损增加,以及光伏和负荷出力的不确定性等问题,本文构建基于二阶锥规划的线性凸优化模型,通过控制有载调压变压器和电容器组动作,以及光伏逆变器和静止无功发生器无功补偿能力约束,对日前日内双时间尺度无功优化模型进行动态分析,在简化求解过程的同时加大找到全局最优解的可能性。提出一种基于混沌学习初始化、非线性收敛因子、最优粒子柯西扰动结合蜘蛛猴算法位置更新方式的改进灰狼优化算法,防止算法陷入局部最优并增强其全局搜索能力。最后,运用改进的灰狼优化算法对含光伏的IEEE 33节点系统进行建模仿真,结果表明该算法具有寻优效率高、收敛速度快的优点,验证了算法的可行性和高效性。In view of the problems caused by photovoltaic grid connection to the distribution network,such as voltage fluctuations,increased line losses,and uncertainty in photovoltaic and load output,this paper constructs a linear convex optimization model based on second-order cone programming.By controlling the on-load voltage regulating transformer and the capacitor bank action,photovoltaic inverter and static var generator reactive power compensation capacity constraints are dynamically analyzed on the day-ahead and intra-day dual time scale reactive power optimization model,which simplifies the solution process and increases the possibility of finding the global optimum.An improved gray wolf algorithm based on chaotic learning initialization,nonlinear convergence factor,optimal particle Cauchy perturbation and spider monkey algorithm position update method is proposed to prevent falling into local optima and enhance global search capabilities.Finally,the algorithm is used to model and simulate the IEEE 33 node system containing photo-voltaic.The results show that the algorithm has the advantages of high optimization efficiency and fast con-vergence speed.The feasibility and effect of the proposed algorithm are confirmed.Keywords:distribution network;photovoltaic power generation;dynamic reactive power optimization;second-order cone programming;gray wolf optimization(GWO)

关 键 词：配电网 光伏发电 动态无功优化 二阶锥规划 灰狼优化算法(GWO) 

分 类 号：TM714.3[电气工程—电力系统及自动化] TM615[自动化与计算机技术—控制理论与控制工程] TP18[自动化与计算机技术—控制科学与工程]