摘要
针对单目标算法收敛性差的问题,提出一种基于自适应网格的哈里斯鹰算法,并应用于含多能量路由器的配电网多目标无功优化。该算法在初始化种群阶段引入Tent混沌映射产生均匀个体,增强种群的多样性,在最佳个体选择和非劣解集的筛选过程中,考虑到哈里斯鹰群体的密度信息,以平衡全局和局部搜索的能力。然后,创建配电网无功优化模型,以有功网损和电压偏离度的最小化为目标函数。该模型采用修改后的IEEE-33标准测试系统作为算例进行仿真分析。仿真结果表明与非支配排序遗传算法和多目标粒子群算法相比,所提算法具有更好的收敛性,在有功网损和电压偏离度2个方面均能取得更好的效果。
In the light of the poor convergence of single objective algorithm,Harris Hawk algorithm based on adaptive grid is proposed for the multi-objective reactive power optimization of distribution network with multi-energy router(MER).Tent chaotic mapping is introduced to generate uniform individuals in the initialization population stage to enhance the diversity of the population,comprehensively considers the density information of Harris Hawks individuals in the selection of optimal individual and trimming of non-inferior solution sets,as well as balances the global and local search capabilities.Then,reactive distribution network optimization model is established with the objective function of minimizing active network loss and voltage deviation.The modified IEEE-33 standard test system is used as an example for simulation analysis.The simulation results show that compared with NSGA-II and MOPSO,the proposed algorithm has better convergence and better performances in two aspects of active network loss and voltage deviation.
作者
从帆平
周建萍
CONG Fanping;ZHOU Jianping(College of Automation Engineering,Shanghai University of Electric Power,Shanghai 200090,China)
出处
《智慧电力》
北大核心
2023年第9期66-73,共8页
Smart Power
基金
国家自然科学基金资助项目(61905139)。
