Operation Reliability Assessment and Diagnosis Method Based on Random Matrix Distribution Network

The reliability and safety of distribution network operation have great significance for daily power supply security. In order to make full use of multi-source distribution network data, diagnose and evaluate the evaluation index of distribution network operation reliability, this paper proposes a long-short-term memory neural network and random matrix operation diagnosis method for distribution network based on the combination of physics and data model. The long-short-term memory neural network and random matrix theory are analyzed first and the long-short-term memory neural network is used to train the node load data to obtain the prediction model. According to the definition of the multilayer physical index system, the system physical index is calculated. The description is established combined with the random matrix. Data indicators for overall operational posture. Principal component analysis is used to extract the main physical indicators and integrate them with the data indicators to obtain the diagnostic indicators for the distribution network operation assessment. The actual operation data proves that the proposed evaluation and diagnosis method can effectively reflect the running state of the urban distribution network, and has good multi-source data application capability and practicability.