Suzhou Electric Appliance Research Institute
期刊號: CN32-1800/TM| ISSN1007-3175

Article retrieval

文章檢索

首頁 >> 文章檢索 >> 文章瀏覽排名

交流XLPE電纜典型絕緣缺陷的PD特性與類型識別

來源:電工電氣發(fā)布時間:2020-06-18 15:18 瀏覽次數(shù):945
交流XLPE電纜典型絕緣缺陷的PD特性與類型識別
 
何若冰1,陳佳2,朱勁松1,楊旭2,姚雨杭3,潘成3,唐炬3
(1 廣東電網(wǎng)有限責任公司陽江供電公司,廣東 陽江 529500;2 國網(wǎng)電力科學研究院武漢南瑞有限責任公司,湖北 武漢 430074;
3 武漢大學 電氣與自動化學院,湖北 武漢 430072)
 
    摘 要:針對交聯(lián)聚乙烯(XLPE) 電纜及其附件常見的9種絕緣缺陷類型,制作了相應的缺陷模型,研究了9種缺陷在不同電壓下的局部放電特性。發(fā)現(xiàn)不同缺陷的譜圖形狀、放電的相位分布等表現(xiàn)出不同特點,每種缺陷的放電重復率與平均放電量均隨著電壓的升高而增大,其中氣隙缺陷的最大放電量和放電重復率高于其他缺陷,電樹枝缺陷的放電重復率最低。對不同缺陷的局部放電譜圖進行了特征量提取,并利用基于L-M算法的BP神經(jīng)網(wǎng)絡,實現(xiàn)了故障類型的識別,最低識別率達到89.17%,取得了較好的識別效果。
    關鍵詞:交聯(lián)聚乙烯(XLPE) 電纜;附件;交流電壓;絕緣缺陷;局部放電;故障識別
    中圖分類號:TM247;TM855     文獻標識碼:A     文章編號:1007-3175(2020)06-0005-09
 
Partial Discharge Characteristics and Type Identification of Typical Insulation Defects of AC XLPE Cables
 
HE Ruo-bing1, CHEN Jia2, ZHU Jin-song1, YANG Xu2, YAO Yu-hang3, PAN Cheng3, TANG Ju3
(1 Guangdong Power Grid Co.,Ltd, Yangjiang Power Supply Company, Yangjiang 529500, China;
2 Wuhan Nari Limited Liability Company of State Grid Electric Power Research Institute, Wuhan 430074, China;
3 School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China)
 
    Abstract: This paper aims at the nine types of insulation defects of AC XLPE cables and accessories, corresponding defect models were made, and the partial discharge characteristics of nine defects at different voltages were studied. It was found that the shape of the spectrum of different defects and the phase distribution of the discharge have different characteristics. The discharge repetition rate and average discharge of each defect increased with the increasing voltage. Among them, the maximum discharge amount and discharge repetition rate of insulation cavity defects were higher than other defects, and the discharge repetition rate of electrical tree defects was the lowest. Feature quantities were extracted from the partial discharge spectra of different defects, and the BP neural network based on the L-M algorithm was used to realize the fault type identification. The minimum recognition rate was 89.17%, and a good recognition effect was achieved.
    Key words: XLPE cable; accessories; AC voltage; insulation defects; partial discharge; fault identification
 
參考文獻
[1] 郭然. 考慮運行風險的輸電電纜外護層絕緣缺陷檢修策略的研究[D]. 廣州:華南理工大學,2017.
[2] 龍紅星. 基于振蕩波局部放電檢測的電纜缺陷類型識別研究[D]. 廣州:華南理工大學,2017.
[3] 林文釗. 基于振蕩波局部放電檢測的電力電纜缺陷定位研究[D]. 廣州:華南理工大學,2016.
[4] SWLTZER-GRANT M, SIEW W H, CORR E, et al. Laboratory and field partial discharge measurement in HVDC power cables[C]/ / Proceedings of the 9th International Conference on Insulated Power Cables(Jicable),2015.
[5] 李曉華,吳廣寧,張血琴,等. 典型缺陷的直流局部放電波形測量與特性分析[J]. 高電壓技術,2007,33(8):31-34.
[6] NIEMEYER L.Ageneralized approach to partial discharge modeling[J]. IEEE Transactions on Dielectrics and Electrical Insulation,1995,2(4):510-528.
[7] 楊豐源,許永鵬,鄭新龍,等. 基于壓縮感知的高壓直流電纜局部放電模式識別[J]. 高電壓技術,2017,43(2):446-452.
[8] 楊孝華. 交聯(lián)聚乙烯電力電纜局部放電模式識別的研究[D]. 重慶:重慶大學,2002.
[9] 沈劍波,雷相東,李玉堂,等. 基于BP神經(jīng)網(wǎng)絡的長白落葉松人工林林分平均高預測[J]. 南京林業(yè)大學學報( 自然科學版),2018,42(2):147-154.
[10] 朱勁夫, 劉明哲, 趙成強, 等. 正則化在邏輯回歸與神經(jīng)網(wǎng)絡中的應用研究[J]. 信息技術,2016(7):1-5.
[11] 王洪,牛曉靈. 基于l2正則化回聲狀態(tài)網(wǎng)絡的模擬電路故障診斷[J]. 電子器件,2017,40(5):1283-1286.