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

Yong Liu (), Yufeng Guo, Bohan Wang, Qiran Li, Qun Gao and Yuanhao Wan
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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

Energies, 2024, vol. 17, issue 11, 1-12

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.

Keywords: wind deflection; stall spacing; height difference; wind speed; wind attack angle; meteorological prediction-based early warning (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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