Investigation of Partial Discharge Phenomena on XLPE Cable Insulation Using COMSOL Multiphysics

Abstract

The presence of various defects including the presence of micro-cavities, cracks, and contamination of impurities intensifies the field stress inside the insulation when subjected to high voltage (HV), which results in the initiation of discharge activity. Therefore, the measurement and analysis of partial discharge (PD) phenomena are essential for the condition assessment of HV insulation. This study focused on the application of COMSOL multi-physics in an XLPE cable insulation sample with an artificially created cavity defect to evaluate the distribution of electric field stress, PD inception, and extinction phenomena. The COMSOL simulation of the XLPE sample is carried out in the presence of a spherical void by considering the effect of void diameter, void position, and influence of harmonics. The study also replicates the influence of varying harmonic content along with total harmonic distortion (THD) which highlights the importance of PD pattern. It has been observed that PDs tend to concentrate in $\left({\mathit{\text{dE}}}_{\mathit{\text{co}}}\left(t\right)/\mathit{\text{dt}}\right),$ particularly in areas with significant slopes. Whereas, local minima act as inhibitors, and distorted the PD pattern which is 300% and 200% higher in 5th and 7th harmonic as compared to 3rd during 20% THD.

Keywords:

• finite element analysis
• partial discharge
• harmonics
• XLPE cable

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Rakesh Sahoo

Rakesh Sahoo was born in India, in 1990. He received the B.Tech. degree in electrical and electronics engineering from the Biju Patnaik University of Technology, Rourkela, India, in 2011, and the M.Tech. degree in electrical engineering from the Veer Surendra Sai University of Technology, Sambalpur, disha, India, in 2014. He is currently pursuing the Ph.D. degree in electrical engineering from the National Institute of Technology Rourkela, Rourkela. His research interests include pattern recognition, electrical and physicochemical characteristics analysis as well as condition monitoring of high-voltage underground cables using machine learning and deep learning methods.

Subrata Karmakar

Subrata Karmakar (Senior Member, IEEE) was born in India, in 1981. He received the bachelor’s degree (Hons.) in electrical engineering from The University of Burdwan, Bardhaman, India, in 2004, and the M.Tech. and Ph.D. degrees from the National Institute of Technology Durgapur, Durgapur, India, in 2006 and 2011, respectively. He is currently an Associate Professor with the Department of Electrical Engineering, National Institute of Technology Rourkela, Rourkela, India. He has published more than 70 research papers. His research interests include condition monitoring of high voltage equipment, dielectrics fluids, detection and localization of faults using signal processing, machine learning, and deep learning technique in high voltage power equipment. Dr. Karmakar is currently a member of IEEE Dielectric and Electrical Insulation Society (DEIS).