Identification and Location of PD Defects in Medium voltage Underground Power Cables Using High Frequency Current Transformer

Fault location is an important diagnostic task in condition monitoring of underground medium voltage cables. Available solutions are well capable of determining the location of a single partial discharge (PD) defect on a cable section. In case several PD defects are active simultaneously along a cable section, the interpretation of the measured data becomes complex to identify the presence of more than one PD sources. In this paper, experimental investigation of two PD defects/sources at different locations on a medium voltage (MV) cable section is presented. A high frequency current transformer is used for single end PD measurements. Time domain reflectometry-based in-depth study of the reflected pulses provides the most valuable information to identify the presence of PD sources which further leads to the location of the individual PD sources. In this paper, the proposed solution is presented for two PD sources, however, the same methodology can be extended to locate multiple PD sources on the cable.

[1]  Muzamir Isa,et al.  Denoising technique for partial discharge signal : A comparison performance between artificial neural network, fast fourier transform and discrete wavelet transform , 2016, 2016 IEEE International Conference on Power and Energy (PECon).

[2]  Yong-June Shin,et al.  Offline Fault Localization Technique on HVDC Submarine Cable via Time–Frequency Domain Reflectometry , 2017, IEEE Transactions on Power Delivery.

[3]  John Daly,et al.  Statistics of AC Underground Cables in Power Networks , 2007 .

[4]  Guillermo Robles,et al.  Multiple Partial Discharge Source Localization in Power Cables Through Power Spectral Separation and Time-Domain Reflectometry , 2019, IEEE Transactions on Instrumentation and Measurement.

[5]  V. Fuster,et al.  Localization techniques of partial discharges at cable ends in off-line single-sided partial discharge cable measurements , 2016, IEEE Transactions on Dielectrics and Electrical Insulation.

[6]  Alfredo Contin,et al.  A NEW METHOD FOR AUTOMATIC MULTIPLE PARTIAL DISCHARGE CLASSIFICATION , 2011 .

[7]  Gavita Mugala.  Influence of the semi-conducting screens on the wave propagation characteristics of medium voltage extruded cables , 2003 .

[8]  Kimmo Kauhaniemi,et al.  Online condition monitoring of MV cable feeders using Rogowski coil sensors for PD measurements , 2019, Electric Power Systems Research.

[9]  Illias Hazlee,et al.  Classification of multiple partial discharge sources in dielectric insulation material using Cepstrum analysis–artificial neural network , 2017 .

[10]  Roger Shuttleworth,et al.  Partial discharge pulse propagation, localisation and measurements in medium voltage power cables , 2013, 2013 48th International Universities' Power Engineering Conference (UPEC).

[11]  Marta Ruiz-Llata,et al.  Identification of multiple partial discharge sources using acoustic emission technique and blind source separation , 2015, IEEE Transactions on Dielectrics and Electrical Insulation.

[12]  Giovanni Mazzanti,et al.  Diagnosis and location of faults in submarine power cables , 2016, IEEE Electrical Insulation Magazine.

[13]  Yan Li,et al.  Temperature dependent signal propagation velocity: possible indicator for mv cable dynamic rating , 2015, IEEE Transactions on Dielectrics and Electrical Insulation.

[14]  Matti Lehtonen,et al.  Effect of Terminating Resistance on High Frequency Behaviour of Rogowski Coil for Transient Measurements , 2013 .

[15]  Simon M. Rowland,et al.  The State of the Art of Condition Monitoring: Where do we go from here? , 2013 .

[16]  R. Sarathi,et al.  Electrical treeing in XLPE cable insulation under harmonic AC voltages , 2015, IEEE Transactions on Dielectrics and Electrical Insulation.

[17]  M. M. Yaacob,et al.  Review on partial discharge detection techniques related to high voltage power equipment using different sensors , 2014 .

[18]  Hazlee Azil Illias,et al.  Partial discharge classifications: Review of recent progress , 2015 .

[19]  M. R. Petraglia,et al.  A new wavelet selection method for partial discharge denoising , 2015 .

[20]  Matti Lehtonen,et al.  Performance evaluation of noise reduction method during on-line monitoring of MV switchgear for PD measurements by non-intrusive sensors , 2015 .

[21]  Yan Li,et al.  Guarding MV cables on-line: With travelling wave based temperature monitoring, fault location, PD location and PD related remaining life aspects , 2016, IEEE Transactions on Dielectrics and Electrical Insulation.