基于多目标鲸鱼算法的配电网动态无功优化研究  

Research on dynamic reactive power optimization of distribution network based on multi-objective whale optimization algorithm

作　　者：夏正龙 陈宇 陆良帅 李灿 张成 Xia Zhenglong;Chen Yu;Lu Liangshuai;Li Can;Zhang Cheng(School of Electrical Engineering and Automation,Jiangsu Normal University,Xuzhou 221116,China)

机构地区：[1]江苏师范大学电气工程及自动化学院,江苏徐州221116

出　　处：《河南师范大学学报（自然科学版）》2025年第1期116-124,I0007,I0008,共11页Journal of Henan Normal University(Natural Science Edition)

基　　金：国家自然科学基金(62103173).

摘　　要：随着光伏、风电等分布式电源大量接入电力系统,对电网的安全性与经济性提出了新的挑战.为了适应风光出力的不确定性,考虑其接入位置对电网的影响,搭建了含风光的配电网动态无功优化模型.采用多目标鲸鱼算法对模型进行求解,将网损、电压偏差进行归一化,选择了其欧氏距离最小的解作为Pareto最优解集的折中解.最后,通过IEEE标准33节点算例进行仿真分析,结果验证了分布式电源的并入能够有效减少系统网损、电压偏差,与其他传统多目标算法相比,所提的算法能够获得分布更均匀、收敛精度更高的Pareto解集.With the large number of distributed generation such as photovoltaic and wind power connected to the power system,the security and economy of the power grid have been challenged.In order to adapt to the uncertainty of wind-landscape output,considering the influence of its access location on the power grid,a dynamic reactive power optimization model of distribution network with wind-landscape is built.The multi-objective whale optimization algorithm is used to solve the model,the network loss and voltage deviation are normalized,and the solution with the smallest Euclidean distance is selected as the compromise solution of Pareto optimal solution set.Finally,through the IEEE standard 33-node simulation,the results verify that the integration of distributed generation can effectively reduce the net-work loss and voltage deviation of the system.Compared with other traditional multi-objective algorithms,the proposed algorithm can obtain a Pareto solution set with more uniform distribution and higher convergence accuracy.

关 键 词：分布式电源 动态无功优化 PARETO解集 多目标鲸鱼算法 

分 类 号：TM761[电气工程—电力系统及自动化]