A rapid warning method for wildfire occurrences along the transmission corridor driven by power system monitoring data - Duan, Xiangxi; Huang, Qi; Chen, Zhe; Li, Jian; Ren, Xibi (Frontiers in Energy Research, 2022)
This paper focuses on the problems of frequent wildfire occurrences along the transmission corridor and the lack of accurate and timely monitoring means for early warnings. Furthermore, this paper evaluates the rapid warning method for wildfire occurrences along the transmission corridor driven by power system monitoring data. First, we established the relationship between the historical data of wildfires along the transmission corridor and the operating state information of a power grid based on the Apriori association rule algorithm; the characteristic signals of the transmission line when wildfires occur were mined. Second, based on the characteristics of the time distribution of wildfire occurrences along the transmission corridor, a nonlinear regression model was created to further improve the prediction accuracy. Finally, by combining the characteristic signals and time distribution characteristics, we developed an early warning method. This method not only addresses the challenges faced by meteorological satellite remote sensors caused by the weather, the long transit time interval, and the high cost of adding sensors, but it also realizes the remote and rapid early warning of wildfires along the transmission corridor. Finally, a case study of practical data of a certain area in southwest China is used to verify the proposed method. The results show the high accuracy and timeliness of the proposed method.