2025年4月3日 周四
首页 > 过刊浏览>2023年第38卷第4期 >198-204. DOI:10.19781/j.issn.1673-9140.2023.04.021
PDF HTML阅读 XML下载 导出引用 引用提醒
500 kV避雷器受潮条件下内部热点温度反演方法
CSTR:
[cstr]
作者:
作者单位:

(1.国网湖北省电力有限公司黄石供电公司，湖北 黄石 435000;2.南瑞集团有限公司(国网电力科学研究院有限公司)，江苏 南京 211106;3.国网电力科学研究院武汉南瑞有限责任公司，湖北 武汉 430074;4.三峡大学电气与新能源学院，湖北 宜昌 443002)

通讯作者:

黎 鹏（1989—），男，博士，副教授，主要从事电力设备故障检测、电工装备多物理场分析等研究；E?mail:lipeng_ctgu@163.com

中图分类号:

TM863

基金项目:

国家自然科学基金(51807110)；国网湖北省电力有限公司科技项目（B715B02100B7）


Internal hot spot temperature inversion method of 500 kV arrester under damp condition
Author:
Affiliation:

(1.Huangshi Power Supply Company, State Grid Hubei Electric Power Co.,Ltd., Huangshi 435000, China;2.NARI Group Co.,Ltd. (State Grid Electric Power Research Institute), Nanjing 211106, China;3.Wuhan NARI Co.,Ltd., State Grid Electric Power Research Institute,Wuhan 430074, China;4. College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China)

  • 摘要
    • | |
  • 访问统计
    • |
  • 参考文献 [20]
    • | | | |
  • 文章评论
    摘要:

    准确预测避雷器内部热点温度，可有效提升避雷器受潮故障的检查效果。为此，提出基于表面温度和SVM的500 kV氧化锌避雷器内部热点温度反演检测方法，以避雷器表面温度和风速作为输入量，实现避雷器内部热点温度的反演。为提高模型预测的准确性，比较网格搜索 (GS)和粒子群 (PSO) 参数寻优算法对反演精度的影响。结果表明：GS?SVM模型的反演性能较好，反演得到的内部热点温度与实际值的最大和最小误差分别为4.00、0.01 ℃，可以证明反演模型的有效性。

    Abstract:

    Accurately predicting the internal hot spot temperature can improve the damp fault inspection effect of arrester effectively. An inversion detection method of hot spot temperature inside 500 kV arrester based on surface temperature and SVM (support vector machine) is proposed. Taking the surface temperature of arrester and wind speed as inputs, the inversion of hot spot temperature inside arrester is realized. In order to improve the prediction accuracy of the proposed model, the influences of the grid search (GS) and particle swarm optimization (PSO) algorithms on inversion accuracy are compared. The results show that the GS?SVM model is of good inversion performance. The maximum and minimum errors between the internal hot spot temperature obtained by the inversion method and the actual values are 4.00 ℃ and 0.01 ℃ respectively, which proves the effectiveness of the inversion model.

    参考文献
    [1] ANDRADE A F,COSTA E G,FERNANDES J M B,et al.Thermal behaviour analysis in a porcelain?housed ZnO surge arrester by computer simulations and thermography[J].High Voltage,2019,4(3):173?177.
    [2] 王小君,毕成杰,金程,等.电气化铁路不停电过分相电磁暂态及抑制措施研究[J].电工技术学报,2021,36(1):191?202. WANG Xiaojun,BI Chengjie,JIN Cheng,et al.Research on electromagnetic transient and suppression measures for passing neutral section without power interruption of electrified railway[J].Transactions of China Electrotechnical Society,2021,36(1):191?202.
    [3] 段长君,闫军,霍峰,等.500 kV金属氧化物避雷器的运行状态带电诊断[J].电力科学与技术学报,2014,29(4):106?110. DUAN Changjun,YAN Jun,HUO Feng,et al.Charged state diagnostic for 500 kV metal oxide arrester[J].Journal of Electric Power Science and Technology,2014,29(4):106?110.
    [4] 夏永强,冯海超,郑智勇.10 kV绝缘导线防断线用避雷器串联羊角间隙的距离确定方法[J].电力科学与技术学报,2019,34(1):136?141. XIA Yongqiang,FENG Haichao,ZHENG Zhiyong.Study on the distance determination method of angle gap in series with an anti?break lightning arrester for 10 kV insulated wires[J].Journal of Electric Power Science and Technology,2019,34(1):136?141.
    [5] 周松霖,段佳奇,齐伟强.基于模糊评判的变电设备评估[J].电力科学与技术学报,2021,36(3):174?179. ZHOU Songlin,DUAN Jiaqi,QI Weiqiang.Substation equipment state evaluation method based on fuzzy comprehensive evaluation[J].Journal of Electric Power Science and Technology,2021,36(3):174?179.
    [6] 陈晓春,周仲康,王康,等.复合绝缘子多因素环境老化性能分析[J].电力科学与技术学报,2017,32(4):90?95. CHEN Xiaochun,ZHOU Zhongkang,WANG Kang,et al.Shed properties analysis of composite insulators under multi?factor aging test[J].Journal of Electric Power Science and Technology,2017,32(4):90?95.
    [7] 刘尉,肖集雄,金硕,等.基于场路耦合的500 kV氧化锌避雷器受潮缺陷分析[J].电瓷避雷器,2022 (1):118?125. LIU Wei,XIAO Jixiong,JIN Shuo,et al.Analysis on damp defect of 500 kV zinc oxide arrester based on field?circuit coupling[J].Insulators and Surge Arresters,2022(1):118?125.
    [8] 黎鹏,屈莹莹,方蓓贝,等.不同故障条件下500 kV金属氧化锌避雷器温度分布特性[J].科学技术与工程,2021,21(9):3649?3655. LI Peng,QU Yingying,FANG Beibei,et al.Calculation of temperature distribution characteristics of 500 kV metal zinc oxide arrester under different fault conditions[J].Science Technology and Engineering,2021,21(9):3649?3655.
    [9] 史志强,段涛,李占峰,等.特高压氧化锌避雷器受潮缺陷试验分析[J].电瓷避雷器,2020 (6):117?121. SHI Zhiqiang,DUAN Tao,LI Zhanfeng,et al.Experimental analysis on dampness defect of UHV zinc oxide arrester[J].Insulators and Surge Arresters,2020(6):117?121.
    [10] 范敏,谢佳,姜方财,等.基于带电检测技术的金属氧化物避雷器缺陷分析[J].电瓷避雷器,2017(2):64?68. FAN Min,XIE Jia,JIANG Fangcai,et al.The defect analysis of MOA on the basic of live detection technology[J].Insulators and Surge Arresters,2017(2):64?68.
    [11] 任大江,叶海鹏,李建萍,等.一起500 kV金属氧化锌避雷器故障原因分析[J].电瓷避雷器,2020 (3):127?132. REN Dajiang,YE Haipeng,LI Jianping,et al.Analysis of the causes of a 500 kV metal zinc oxide arrester fault[J].Insulators and Surge Arresters,2020(3):127?132.
    [12] 王宏刚,纪鑫,武同心,等.基于预训练语言模型的电力领域设备缺陷检测[J].电测与仪表,2022,59(5):180?186. WANG Honggang,JI Xin,WU Tongxin,et al.Device defect detection in power field based on pre?trained language model[J].Electrical Measurement & Instrumentation,2022,59(5):180?186.
    [13] 段建家,何智强,范敏.一起500 kV金属氧化物避雷器事故分析[J].电瓷避雷器,2014(3):79?83. DUAN Jianjia,HE Zhiqiang,FAN Min.Analysis on a 500 kV metal oxide arrestor accident[J].Insulators and Surge Arresters,2014(3):79?83.
    [14] ZHANG P P,SHI W,WANG H.Simulation of potential distribution and leakage current of 800 kV DC arrester under different degree of degradation[J].IOP Conference Series:Materials Science and Engineering,2019,486(1):1?6.
    [15] 沈越,彭劲樟,张再华,等.500 kV避雷器受潮情况下温升计算及影响因素分析[J].水电能源科学,2023,41(6):211?215. SHEN Yue,PENG Jinzhang,ZHANG Zaihua,et al.Calculation of temperature rise of 500 kV arrester under damp condition and analysis of influencing factors[J].Water Resources and Power,2023,41(6):211?215.
    [16] GAO X,HOU J.An improved SVM integrated GS?PCA fault diagnosis approach of tennessee eastman process[J].Neurocomputing,2016,174:906?911.
    [17] 何邦乐,黄勇,叶頲,等.基于PSO?LSSVM的高压电力电缆接头温度预测[J].电力工程技术,2019,38(1):31?35. HE Bangle,HUANG Yong,YE Ting,et al.Temperature prediction of power cable joint based on PSO?LSSVM predict model[J].Electric Power Engineering Technology,2019,38(1):31?35.
    [18] 甘锡淞,傅成华,余洋.基于模糊环境AMPSO?SVM氧化锌避雷器故障诊断研究[J].电瓷避雷器,2017(5):41?463. GAN Xisong,FU Chenghua,YU Yang. Study on fault diagnosis for zinc oxide arrester based on hybridfuzzy environment AMPSO?SVM[J].Insulators and Surge Arresters,2017(5):41?46.
    [19] 邱志斌,阮江军,黄道春,等.直流导线和阀厅金具的电晕起始电压预测[J].电工技术学报,2016,38(8):80?89. QIU Zhibin,RUAN Jiangjun,HUANG Daochun,et al.Prediction on corona onset voltage of dc conductors and valve hall fittings[J].Transactions of China Electrotechnical Society,2016,38(8):80?89.
    [20] 黎鹏,刘畅,吴泳聪,等.基于NSGA?Ⅱ算法的高压开关柜泄压通道优化设计[J].高电压技术,2020,46(6):2013?2020. LI Peng,LIU Chang,WU Yongcong,et al.Optimization design of pressure relief channel for HV switchgear based on NSGA?Ⅱ[J].High Voltage Engineering,2020,46(6):2013?2020.
    相似文献
    引证文献
    网友评论
    网友评论
    分享到微博
    发 布
引用本文

彭劲樟,张再华,吴风亮,等.500 kV避雷器受潮条件下内部热点温度反演方法[J].电力科学与技术学报,2023,38(4):198-204.
PENG Jingzhang, ZHANG Zaihua, WU Fengliang, et al. Internal hot spot temperature inversion method of 500 kV arrester under damp condition[J]. Journal of Electric Power Science and Technology,2023,38(4):198-204.

复制
分享
文章指标
  • 点击次数:127
  • 下载次数: 610
  • HTML阅读次数: 0
  • 引用次数: 0
历史
  • 在线发布日期: 2023-11-06
文章二维码

微信公众号二维码

您是本站第 83136 访问者

通信地址：长沙市（天心区）万家丽南路960号长沙理工大学

电话/传真：0731-85258195 E-mail：dlxb04@163.com

版权所有：电力科学与技术学报 ® 2025 版权所有

京公网安备 11010802026262号