Semimonthly
ISSN 1000-1026
CN 32-1180/TP
Semimonthly
ISSN 1000-1026
CN 32-1180/TP
HOU Hui
School of Automation, Wuhan University of Technology, Wuhan 430070, ChinaYU Shiwen
School of Automation, Wuhan University of Technology, Wuhan 430070, ChinaLI Xianqiang
School of Automation, Wuhan University of Technology, Wuhan 430070, ChinaWANG Hongbin
Guangzhou Power Supply Bureau Co., Ltd., Guangzhou 510620, ChinaHUANG Yong
Electric Power Research Institute, Guangdong Power Grid Co., Ltd., Guangzhou 510080, ChinaWU Xixiu
School of Automation, Wuhan University of Technology, Wuhan 430070, China1.School of Automation, Wuhan University of Technology, Wuhan 430070, China;2.Guangzhou Power Supply Bureau Co., Ltd., Guangzhou 510620, China;3.Electric Power Research Institute, Guangdong Power Grid Co., Ltd., Guangzhou 510080, China
To address the problem of low prediction accuracy and data utilization rate of transmission line damage under typhoon disaster, a hybrid model for the probability prediction of transmission line damage based on random wind field probability weighting is built. This model comprehensively considers the fusion of spatial multi-source heterogeneous information such as weather, micro-topography, tower operation, and real-time damage. Firstly, the Gumbel distribution is used to simulate the wind value of gusts, and Kolmogorov-Smirnov test proves its high accuracy. Secondly, the Monte Carlo method is used to realize the probability generation of random wind fields. Finally, the random forest method is used to predict the probability of line damage in each wind field, realizing the probability prediction of transmission line damage based on random wind field probability weighting. The prediction result can provide effective early warning decision support for the sectors of power industry. An example of the typhoon “Mangkhut” verifies the scientific nature and validity of the proposed hybrid model for the probability prediction of transmission line damage based on random wind field probability weighting.
| [1] | HOU Hui, YU Shiwen, LI Xianqiang, et al. Early Warning for Transmission Line Damage Under Typhoon Disaster Based on Random Wind Field Probability Weighting[J]. Automation of Electric Power Systems,2021,45(7):140-147. DOI:10.7500/AEPS20200115021 |
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