基于PSO-ELM的变压器油纸绝缘状态无损评估方法  

The assessment method of transformer oil-paper insulation state based on PSO-ELM

作　　者：张德文 张健 曲利民 吴迪星 刘贺千 张明泽[2] ZHANG Dewen;ZHANG Jian;QU Limin;WU Dixing;LIU Heqian;ZHANG Mingze(State Grid Heilongjiang Electric Power Co.,Ltd.Research Institute,Harbin 150030,China;Harbin University of Science and Technology(Key Laboratory of Engineering Dielectrics and Its Application,Ministry of Education),Harbin 150080,China)

机构地区：[1]国网黑龙江省电力有限公司电力科学研究院,黑龙江哈尔滨150030 [2]哈尔滨理工大学(工程电介质及其应用教育部重点实验室),黑龙江哈尔滨150080

出　　处：《电力工程技术》2024年第3期201-208,共8页Electric Power Engineering Technology

基　　金：国家电网有限公司科技项目(5500-202330167A-1-1-ZN);国家自然科学基金资助项目(52307164)。

摘　　要：油浸式电力变压器作为电网的重要组成部分,其可靠运行至关重要。针对变压器长期运行后无法定量评估其绝缘状态的问题,文中开展了油纸绝缘模型的加速老化及受潮试验,探究了油纸绝缘老化及受潮程度对其回复电压曲线的影响规律,并提出采用粒子群优化-极限学习机(particle swarm optimization-extreme learning machine,PSO-ELM)算法的参数预测方法,实现了基于回复电压曲线特征参量的油纸绝缘老化与受潮状态量化评估。由油纸绝缘模型理化性能分析的对比结果可知,基于PSO-ELM方法的预测值精度远高于传统ELM方法,油纸绝缘内含水率及纸板聚合度预测的绝对误差范围分别小于±0.4%、±30。Oil-immersed power transformer is an important part of power grid,and its reliable operation plays a vital role in pomler system security.Aiming at the problem that the insulation state of transformer cannot be assessed quantitatively after long-term operation,the accelerated aging and damp tests of oil-paper insulation model are carried out in this paper.The influence of aging and damp of oil-paper insulation on its recovery voltage curves is explored.The particle swarm optimization(PSO) is used to improve the parameter prediction method of extreme learning machine(ELM),which realizes the quantitative assessment of aging and moisture of oil-paper insulation based on the characteristic parameters of the recovery voltage curve.By comparing the physical and chemical performance analysis of oil-paper insulation models,it is shown that the prediction accuracy of PSO-ELM method is much higher than that of traditional ELM method.The absolute error range for predicting the moisture content of oil-paper insulation the degree of polymerization(DP) of pressboard is less than ±0.4% or ±30,respectively.

关 键 词：油浸式变压器 油纸绝缘 回复电压 粒子群优化-极限学习机(PSO-ELM)算法 状态评估 无损检测 

分 类 号：TM85[电气工程—高电压与绝缘技术]