Research on anomaly identification method for power grid transmission channels based on spatial data

Ultra high voltage power lines transmit large-scale electricity to economically developed areas and are currently an important carrier for long-distance power transmission. High voltage overhead lines are one of the main modes of power transmission. Due to the influence of natural environment and human activities, the transmission channel space faces various risks, and it is necessary to promptly investigate and alert potential risks. In response to this issue, this paper proposes a method for identifying anomalies in power grid transmission channels based on spatial data. Real time monitoring data of transmission channels is obtained through acquisition devices such as cameras and locators. Then, the image, video, geographic information and other data are associated and mapped, and a data model of the transmission channel is constructed with the device as the description core. Under extreme weather conditions such as strong wind, rainstorm and snowstorm, the power transmission channel is disturbed by floating objects and light objects in the nature, causing leakage, short circuit and other problems. Based on the established data model, simulate the movement trajectory of various floating objects that may occur, and then simulate and calculate their various impacts on the safety of transmission channels. Digitally deduce the scope of impact and the secondary accidents caused and determine the impact range of transmission channel risks caused by this event on power supply capacity failures.