自适应模拟退火混合粒子群算法的配电网故障定位  

Fault location in distribution network based on adaptivesimulated annealing hybrid particle swarm algorithm

作　　者：钱程 王爱元(指导)[1,2] 姚晓东 QIAN Cheng;WANG Aiyuan;YAO Xiaodong(School of Electrical Engineering,Shanghai Dianji University,Shanghai 201306,China;Foshan Gaoming Minge New Type Motor Electronic Control Research Institute,Foshan 528500,Guangdong,China)

机构地区：[1]上海电机学院电气学院,上海201306 [2]佛山市高明区明革新型电机电控研究所,广东佛山528500

出　　处：《上海电机学院学报》2022年第4期187-194,共8页Journal of Shanghai Dianji University

基　　金：国家自然科学基金资助项目(61973209)。

摘　　要：针对传统配电网故障定位模型结果精度低的问题,提出一种基于自适应模拟退火混合粒子群算法的故障定位方法。首先,分析实际情况,改进开关节点状态值,在此基础上构造故障模型开关函数。然后,基于模拟退火算法收敛速度快的特性,结合混合粒子群算法搜索范围广的优点,实现两种算法的结合。为了避免陷入局部最优解,引入自适应寻优方案进行迭代判别。接着,分析改进算法故障定位原理,构建适应度函数。最后,对产生的多种故障情况通过Matlab进行算例仿真分析。仿真结果表明:改进算法在配电网故障定位的过程中收敛速度和精度均有明显提高,并针对不同的情况具有一定鲁棒性。To solve the problem of low accuracy of the traditional distribution network fault location model,a fault location method based on adaptive simulated annealing hybrid particle swarm optimization is proposed.First,the actual situation is analyzed,the state value of the switch node is improved,and the fault model switch function is constructed on this basis.Second,based on the fast convergence speed of the simulated annealing algorithm,and a wide search range of the hybrid particle swarm optimization,the combination of the two algorithms is realized.In order to avoid falling into the local optimal solution,an adaptive optimization scheme is introduced for iterative discrimination. Then, the fault location principle of the improved algorithm is analyzed, and a fitness function is constructed. Finally, the various fault conditions generated are simulated and analyzed by Matlab. The simulation results show that the improved algorithm can significantly increase the convergence speed and accuracy in the process of distribution network fault location, and has certain robustness for different situations.

关 键 词：模拟退火算法 混合粒子群算法 自适应寻优方案 有源配电网 故障定位 

分 类 号：TM712[电气工程—电力系统及自动化]