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Research on Influencing Factors and Wind Deflection Warning of Transmission Lines Based on Meteorological Prediction

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Listed:
  • Yong Liu

    (Key Laboratory of the Ministry of Education on Smart Power Grids, School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China)

  • Yufeng Guo

    (Key Laboratory of the Ministry of Education on Smart Power Grids, School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China)

  • Bohan Wang

    (Key Laboratory of the Ministry of Education on Smart Power Grids, School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China)

  • Qiran Li

    (Tangshan Power Supply Company of State Grid Jibei Electric Power Co., Ltd., Tangshan 063099, China)

  • Qun Gao

    (Chengnan District Power Supply Company of State Grid Tianjin Electric Power Co., Ltd., Tianjin 300201, China)

  • Yuanhao Wan

    (Electric Power Research Institute State Grid Xinjiang Co., Ltd., Urumqi 830063, China)

Abstract

Transmission lines are affected by external environmental factors such as strong winds and ice cover. In recent years, extreme weather events have increased, leading to recurrent disturbances in transmission lines because of wind deflection. These incidents have resulted in significant financial losses and have disrupted regular industrial and domestic activities. In this paper, the ANSYS Workbench 2020 R2 finite element analysis platform was used to establish a transmission line-hanging insulator string system model. Calculations on transmission lines were conducted considering variations in different stall spacing, height differences, wind speed, and the wind attack angle. The impact of these diverse factors on the wind deflection of insulators was scrutinized, leading to the derivation of patterns describing how the wind deflection angle shifts in response to changes in stall spacing, height differences, wind speed, and the wind attack angle. Based on the generalized linear regression network and particle swarm improved support vector machine algorithm, a meteorological prediction-based early warning method for wind deflection of transmission lines was proposed, a transmission line wind deflection early warning model was established, and the practical effect of the model was evaluated. The outcomes of this study provide crucial data for the formulation and development of ultra-high voltage (UHV) and extra-high voltage (EHV) transmission networks. Furthermore, they can contribute to the advanced detection of wind deflection issues.

Suggested Citation

  • Yong Liu & Yufeng Guo & Bohan Wang & Qiran Li & Qun Gao & Yuanhao Wan, 2024. "Research on Influencing Factors and Wind Deflection Warning of Transmission Lines Based on Meteorological Prediction," Energies, MDPI, vol. 17(11), pages 1-12, May.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:11:p:2612-:d:1404113
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    References listed on IDEAS

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    1. Xinsheng Dong & Guanru Wen & Mingguan Zhao & Yang Yang & Meng Li & Long Zhao, 2023. "Study of the Prevention Method of ±800 kV Transmission Tower Foundation Deviation," Energies, MDPI, vol. 16(6), pages 1-17, March.
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