摘要
针对基本粒子群算法(particle swarm optimization algorithm,PSO)局部寻优能力差及易早熟收敛的情况,提出一种融入模拟退火思路的自适应粒子群混合算法(simulated annealing-adaptive particle swarmoptimization algorithm,SA-APSO),在惯性权重变化-自适应粒子群基础上融入退火思想,以一定的随机概率接收最优值,能有效提升全局寻优能力并克服早熟收敛现象。利用测试函数进行的仿真结果表明SA-APSO算法在结果精度及稳定度上明显优于基本PSO。并将其应用于变压器油中局部放电的定位计算,将结果与基本PSO及自适应粒子群进行比较,结果表明基于SA-APSO的变压器油中局部放电超声定位方法能够实现全局精确定位,且结果稳定,综合误差小于3.7 mm。
In allusion to the basic particle swarm optimization algorithm local search optimization ability is poor and it is easy to premature convergence,an improved PSO,which integrate simulated annealing idea into the adaptive particle swarm optimization algorithm,is proposed.It is named simulated annealing-adaptive particle swarm optimization algorithm(SA-APSO),based on the adaptive particle swarm optimization,it integrates the simulated annealing idea and accept the optimal value with certain probability.SA-APSO can effectively enhance the global searching ability and overcome the premature convergence phenomenon.The simulation results show that the SA-APSO algorithm is superior to the basic PSO in the accuracy and stability of the results.And its application in location of partial discharge in transformer oil is calculated,the results with the basic PSO and adaptive particle swarm optimization are compared.The results show that based on SA-APSO transformer oil partial discharge-ultrasonic positioning method can realize the accurate global localization and stable result,the synthetic error less than 3.7 mm.
作者
徐艳春
王泉
李振兴
李振华
吕密
XU Yanchun;WANG Quan;LI Zhenxing;LI Zhenhua;LYU Mi(Key Laboratory of Operation and Control of Cascade Hydropower Stations in Hubei Province,Three Gorges University,Hubei Yichang 443002,China;Texas A &M University,College of Electrical Engineering and Computer,Texas 75503,America)
出处
《高压电器》
CAS
CSCD
北大核心
2018年第12期143-149,共7页
High Voltage Apparatus
基金
教育部留学回国人员科研启动基金(KJ2015QT007)
三峡大学研究生科研创新基金(SDYC2016046).
关键词
粒子群算法
SA—APSO算法
变压器
局部放电
超声波
定位
particle swarm optimization algorithm
SA-APSO algorithm
transformer
partial discharge
ultrasonic
localization
