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Location prediction model of zero value insulator based on PNN

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Abstract

Zero insulators directly reduce the electrical performance of insulator strings, affecting the safe and reliable operation of transmission lines. The grounding current of the insulator string contains the characteristic information of insulator electrical performance. Extracting the characteristic information of grounding current can realize the detection of zero value insulator, which is of great significance to ensure the safe operation of transmission lines. In this paper, the composite insulator used on ultra-high-voltage (UHV) lines is studied to analyze the influence of zero insulators on the electric field distribution. Furthermore, the corresponding characteristics of the zero insulators at different locations are extracted. The fitting relationship between the characteristic quantity and the zero insulator position is analyzed. The effective characteristics of grounding current are selected as training sample to establish the zero insulator position prediction model based on probabilistic neural network (PNN). The research result is meaningful for the detection of zero insulators.

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Funding

This work was supported in part by the Key Laboratory of Special Machine and High Voltage Apparatus (Shenyang University of Technology), Ministry of Education under Grant KFKT202111; Shandong Provincial Natural Science Foundation under Grant ZR2021ME057.

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Authors and Affiliations

  1. College of Electric and Electronic Engineering, Shandong University of Technology, Zibo, 255000, China

    Baina He, Shuo Wu, Fantao Meng & Yang Liu

  2. State Grid Shandong Electric Power Company Qingzhou Power Supply Company, Qingzhou, 262500, China

    Lemiao Wang

  3. State Grid Shandong Electric Power Company Jining Power Supply Company, Jining, 272000, China

    Jingru Zhang

  4. Key Laboratory of Special Machine and High Voltage Apparatus, Ministry of Education, Shenyang University of Technology, Shenyang, 110000, China

    Xin Lin

Authors
  1. Baina He
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  2. Shuo Wu
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  3. Lemiao Wang
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  4. Jingru Zhang
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  5. Xin Lin
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  6. Fantao Meng
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  7. Yang Liu
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Contributions

He was a major contributor in writing the manuscript. Wu and Wang performed the simulation examination. Meng and Liu analyzed and interpreted the simulation results. Zhang is responsible for data recording, and Lin is responsible for checking. All authors reviewed and approved the final manuscript.

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Correspondence to Baina He.

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He, B., Wu, S., Wang, L. et al. Location prediction model of zero value insulator based on PNN. Electr Eng 105, 2347–2360 (2023). https://doi.org/10.1007/s00202-023-01794-7

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  • DOI: https://doi.org/10.1007/s00202-023-01794-7

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