Research on lightning strike warning of overhead transmission lines by integrating PMU data

Lightning strike tripping accidents on power transmission lines have occurred repeatedly, causing serious economic losses. To find out the precise location of lightning strikes in transmission lines and to provide early warning of lightning strike tripping phenomena are of great significance to transmission line operation monitoring. The traditional lightning strike warning has a certain lack of accuracy. This paper innovatively proposes Monte Carlo method of transmission line lightning strike warning incorporating PMU data. This method first completes the filtering and noise reduction of PMU data to derive real-time changes in line parameter values. Then, on this basis, it deduces whether the line is tripped and achieves accurate fault location and determines whether the tripping phenomenon is related to the weather based on real-time falling lightning point data. Finally, the improved Fuzzy C-mean clustering algorithm (IFCM) is used to obtain the center of mass of cloud clusters and the density of falling lightning points, combined with the Monte Carlo method to determine the probability value of lightning strikes on transmission lines within a short period of time. Simulation results show that the proposed method can find out the probability value of lightning strike under the limited data conditions and realize the graded lightning strike warning according to the derived probability value, which can guarantee the safety of transmission lines to the maximum extent.