EDGE-CLOUD COLLABORATIVE FAULT DETECTION METHOD FOR LOW-VOLTAGE DISTRIBUTION NETWORK BASED ON RANDOM MATRIX THEORY

The present invention discloses an edge-cloud collaborative fault detection method for a low-voltage distribution network based on a random matrix theory. An edge-cloud collaborative way is adopted, including fast fault detection running in an edge IoT agent and fault timing and locating analysis running in a distribution network control center. At an edge IoT terminal, the fault is quickly detected based on time-delay correlation analysis, a long-time series model is constructed, a time series is fitted with an autoregressive moving average model, and the fault is quickly judged based on a typical value of a limit spectral density function of the time series; after the edge IoT terminal detects the fault, fault-related data are uploaded to the distribution network control center through data screening, historical data and real-time data are integrated, and a spectral deviation index is configured to perform fault timing and locating analysis.