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Charge-Simulation-Based Electric Field Analysis and Electrical Tree Propagation Model with Defects in 10 kV XLPE Cable Joint

Author

Listed:
  • Jiahong He

    (School of Electric Engineering, Southeast University, Nanjing 210096, Jiangsu, China)

  • Kang He

    (School of Electric Engineering, Southeast University, Nanjing 210096, Jiangsu, China)

  • Longfei Cui

    (NR Electric Company Limited, Nanjing 211102, China)

Abstract

The most severe partial discharges and main insulation failures of 10 kV cross-linked polyethylene cables occur at the joint due to defects caused by various factors during the manufacturing and installation processes. The electric field distortion is analyzed as the indicator by the charge simulation method to identify four typical defects (air void, water film, metal debris, and metal needle). This charge simulation method is combined with random walk theory to describe the stochastic process of electrical tree growth around the defects with an analysis of the charge accumulation process. The results illustrate that the electrical trees around the metal debris and needle are more likely to approach the cable core and cause main insulation failure compared with other types of the defects because the vertical field vector to the cable core is significantly larger than the field vectors to other directions during the tree propagation process with conductive defects. The electric field was measured around the cable joint surface and compared with the simulation results to validate the calculation model and the measurement method. The air void and water film defects are difficult to detect when their sizes are less than 5 mm 3 because the field distortions caused by the air void and water film are relatively small and might be concealed by interference. The proposed electric field analysis focuses on the electric field distortion in the cable joint, which is the original cause of the insulation material breakdown. This method identifies the defect and predicts the electrical tree growth in the cable joint simultaneously. It requires no directly attached or embedded sensors to impact the cable joint structure and maintains the power transmission during the detection process.

Suggested Citation

  • Jiahong He & Kang He & Longfei Cui, 2019. "Charge-Simulation-Based Electric Field Analysis and Electrical Tree Propagation Model with Defects in 10 kV XLPE Cable Joint," Energies, MDPI, vol. 12(23), pages 1-22, November.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:23:p:4519-:d:291648
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    References listed on IDEAS

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    1. Fan Yang & Ningxi Zhu & Gang Liu & Hui Ma & Xiaoyu Wei & Chuanliang Hu & Zhenhua Wang & Jiasheng Huang, 2018. "A New Method for Determining the Connection Resistance of the Compression Connector in Cable Joint," Energies, MDPI, vol. 11(7), pages 1-19, June.
    2. Fan Yang & Kai Liu & Peng Cheng & Shaohua Wang & Xiaoyu Wang & Bing Gao & Yalin Fang & Rong Xia & Irfan Ullah, 2016. "The Coupling Fields Characteristics of Cable Joints and Application in the Evaluation of Crimping Process Defects," Energies, MDPI, vol. 9(11), pages 1-19, November.
    3. Li Zhang & Xiyue LuoYang & Yanjie Le & Fan Yang & Chun Gan & Yinxian Zhang, 2018. "A Thermal Probability Density–Based Method to Detect the Internal Defects of Power Cable Joints," Energies, MDPI, vol. 11(7), pages 1-13, June.
    4. WenWei Zhu & YiFeng Zhao & ZhuoZhan Han & XiangBing Wang & YanFeng Wang & Gang Liu & Yue Xie & NingXi Zhu, 2019. "Thermal Effect of Different Laying Modes on Cross-Linked Polyethylene (XLPE) Insulation and a New Estimation on Cable Ampacity," Energies, MDPI, vol. 12(15), pages 1-22, August.
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