Abstract: The present invention discloses a disaster prevention, early warning and production decision support method and system for a power distribution network, and relates to the technical field of the power distribution network. Various data is fused, a maximum wind load, a lightning trip-out rate, a maximum carrying capacity at a highest operation temperature and an average failure frequency and time under an environmental factor are calculated, and a power outage risk is evaluated and classified; and after an emergency, a power grid topology is analyzed, and a device outage probability is calculated to obtain a load power outage probability and risk and provide disaster early warning, monitoring and rush repair decision support.

Abstract: The present invention discloses a flooding water level monitoring method and system for power facilities, including after receiving a flooding emergency response notification and a heavy rainfall defense alarm, starting facility flooding water level monitoring; and based on the individual area and total area of facilities affected by flooding and water level sensing monitoring information, establishing a neural network measuring an affected range, and outputting the monitoring result of a flooded surface height in a region, thereby achieving all-weather real-time monitoring, and accurately measuring and timely reporting a flooding height.

Abstract: Amendment to the Abstract: Disclosed are an in-place supervision method and apparatus suitable for overhead transmission line maintenance operation, the method includes: geographic coordinate information of an overhead transmission line is, written into a risk management and control master station system of the whole electric power operation process, and an in-place supervision algorithm is written into the risk management and control master station system of the whole electric power operation process; geodetic coordinates A of a maintenance operation site and geodetic coordinates B of a supervisor are read; a distance is solved based on an elliptic spherical arc length approximate chord length algorithm; whether the distance S exceeds a threshold value of out of supervision or not is judged.