Deep learning-based power distribution network risk assessment method under incomplete structural parameters

A deep-learning-based power distribution network risk assessment method under incomplete structural parameters comprises the steps: 1) performing statistics on external obtainable historical operationdata of an area with incomplete structural parameter information in a power distribution network, and adopting deep learning training to establish an equivalent packaging model of the historical operation data; 2) according to weather data and electricity price data of a region where the day-ahead prediction is located, substituting the weather data and the electricity price data into an equivalent model, and predicting probability distribution of gateway interaction power between the region with incomplete structure parameter information and the power distribution network; 3) constructing equivalent estimation points and performing power distribution network probabilistic load flow calculation; and 4) performing statistics on probability distribution of state variables in the power distribution network to comple