Investigation of partial discharge characteristics in XLPE cable insulation under increasing electrical stress

被引:9
作者
Choudhary, Maninder [1 ]
Shafiq, Muhammad [2 ]
Kiitam, Ivar [1 ]
Palu, Ivo [1 ]
Hassan, Waqar [3 ]
Singh, Praveen Prakash [1 ]
机构
[1] Tallinn Univ Technol, Dept Elect Power Engn & Mechatron, Tallinn, Estonia
[2] Florida State Univ, Tallahassee, FL USA
[3] Univ Tenaga Nas, Inst Power Engn IPE, Kajang, Malaysia
关键词
XLPE cable; Partial discharge measurement; PD characteristics; Regression analysis; CLASSIFICATION;
D O I
10.1016/j.engfailanal.2024.108006
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Insulation degradation in power components is a looming issue that can have a significant impact on the reliability of power system if not attended timely. Partial discharge (PD) diagnostics is a key technique used for the condition monitoring and health assessment of insulation. Inception of PD is a primary indicator which shows degradation and decreased local dielectric strength of the insulation. PD magnitude can increase with time and level of stress, which may result in failure of insulation. This article investigates the behavior of PD characteristics in a medium voltage (MV) cross-linked polyethylene (XLPE) cable sample, containing a defect at the cable termination, under elevated electrical stresses. PD behavior is studied by investigating the key PD characteristics, such as partial discharge inception voltage (PDIV), phase of occurrence (phi), mean amplitude (V-mean), pulse repetition rate (PRR), and phase span (phi(span)). These quantities are extracted from a phase-resolved partial discharge (PRPD) pattern using a pulse detection algorithm. Later, these characteristics are analyzed in correlation with the electrical stress. Various regression models are implemented and compared to find the best fit model that represents trending attributes of major PD characteristics. The presented study can be used as an effective process to analyze the measured PD data for evaluation of the insulation condition in the power components.
引用
收藏
页数:14
相关论文
共 30 条
[21]  
Neter J., 1985, Applied Linear Statistical Models, V2nd ed.
[22]  
Nguyen H.V.P., 2018, High Voltage
[23]  
Park S.-H., 2008, INT C CONDITION MONI
[24]   Pulse sequence analysis - a diagnostic tool based on the physics behind partial discharges [J].
Patsch, R ;
Berton, F .
JOURNAL OF PHYSICS D-APPLIED PHYSICS, 2002, 35 (01) :25-32
[25]   Trends in partial discharge pattern classification: A survey [J].
Sahoo, NC ;
Salama, MMA ;
Bartnikas, R .
IEEE TRANSACTIONS ON DIELECTRICS AND ELECTRICAL INSULATION, 2005, 12 (02) :248-264
[26]   A tutorial on Gaussian process regression: Modelling, exploring, and exploiting functions [J].
Schulz, Eric ;
Speekenbrink, Maarten ;
Krause, Andreas .
JOURNAL OF MATHEMATICAL PSYCHOLOGY, 2018, 85 :1-16
[27]   A tutorial on support vector regression [J].
Smola, AJ ;
Schölkopf, B .
STATISTICS AND COMPUTING, 2004, 14 (03) :199-222
[28]   A Denoising Algorithm for Partial Discharge Measurement Based on the Combination of Wavelet Threshold and Total Variation Theory [J].
Tang, Ju ;
Zhou, Siyuan ;
Pan, Cheng .
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2020, 69 (06) :3428-3441
[29]   Evaluation of surface changes in flat cavities due to ageing by means of phase-angle resolved partial discharge measurement [J].
Temmen, K .
JOURNAL OF PHYSICS D-APPLIED PHYSICS, 2000, 33 (06) :603-608
[30]   Measurement and Diagnosis of PD Characteristics of Industrial Cable Terminations in Extreme Cold Environment [J].
Zhou, Lijun ;
Bai, Longlei ;
Zhang, Jingkang ;
Cao, Weidong ;
Xiang, Enxin .
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2021, 70