The application discloses a fault
processing technology for a "double-high" type novel power distribution network. The method first constructs a fault
database covering multiple scenes based on short-circuit calculation and a fault sample generation mechanism; then,
voltage /
current time series are normalized and polar
coordinate mapping is performed, and Gramian Angular Summation Field (GASF) is used to convert the
time series into a two-dimensional image; further, a
convolutional neural network is used to extract multi-channel image features and output fault categories; finally, according to the fault categories and short-circuit current levels, the
pickup current and time scale coefficient of the directional
overcurrent relay are updated online, and a nonlinear optimization model is established under the condition of constraining the coordination time interval of the main and standby relays to solve the optimal
relay setting value of the minimum total action time. Compared with the traditional fixed setting value scheme, the application can significantly improve the fault classification accuracy and protection action speed of the power distribution network and realize adaptive protection coordination under a complex source-network-load-storage scene.