Application of deep learning network in power anomaly detection of big data

With the rapid development of power system, the scale of power big data has become increasingly large, and the detection of power consumption anomalies has become an important part of power system management and maintenance. Therefore, this paper proposes a solution of power big data anomaly detection system based on deep learning network. In order to realize the efficient operation of the system, four modules of power consumption fluctuation calculation, embedded vector mapping, feature signal extraction and random forest anomaly discrimination are studied and designed. The experimental results show that the system has excellent performance in the accuracy of abnormal detection, real-time early warning and abnormal event recognition, and has high practical value, which is expected to provide a strong guarantee for the safe operation of the power system.