摘要
针对改进的遗传算法、二进制粒子群算法等智能优化算法在复杂的有源配电网中故障定位的准确率不高、易于陷入局部最优、收敛速度慢以及定位时间长等问题,提出一种基于改进哈里斯鹰优化算法的有源配电网故障区段定位方法。首先,通过Tent混沌映射改善初始种群和将逃逸能量非线性化,以加快哈里斯鹰优化算法的收敛速度。其次,通过结合黄金正弦算法跳出局部最优。最后,所提方法在IEEE33节点有源配电网模型上进行了仿真测试验证,表明改进后的哈里斯鹰优化算法能很大程度地加快收敛速率,故障定位方法具有很高的容错率。
To address the problems that the improved genetic algorithm,binary particle swarm algorithm and other intelligent optimization algorithms have low accuracy,easy to fall into local optimum,slow convergence speed and long localization time for fault location in complex active distribution networks,a fault section location method for active distribution networks based on the improved Harris hawk optimization algorithm is proposed.Firstly,the initial population is improved and the escape energy is nonlinearized by Tent chaotic mapping to accelerate the convergence speed of Harris hawk optimization algorithm.Secondly,the local optimum is jumped out by combining the golden sine algorithm.Finally,the proposed method is validated by simulation tests in an IEEE 33-node active distribution network model.The results show that the improved Harris Hawk optimization algorithm can largely accelerate the convergence rate,and the proposed fault location method has high fault tolerance rate.
作者
麦章渠
曾颖
张禄亮
李晨涛
季天瑶
尚筱雅
MAI Zhangqu;ZENG Ying;ZHANG Luliang;LI Chentao;JI Tianyao;SHANG Xiaoya(School of Electric Power,South China University of Technology,Guangzhou 510640,China;School of Naval Architecture and Ocean Engineering,Guangzhou Maritime University,Guangzhou 510725,China)
出处
《智慧电力》
北大核心
2022年第11期104-111,共8页
Smart Power
基金
国家自然科学基金资助项目(52077081)
广东省基础与应用基础研究基金项目(2022A1515011587)
广州市科技计划项目(202102020663)。
关键词
有源配电网
故障定位
哈里斯鹰优化算法
信息畸变
active distribution network
fault location
Harris hawk optimization algorithm
information distortion
