Research on automatic checking method of power anomaly data based on chaotic sequence

Abstract

With the increasing complexity and scale of power system, the challenges of data management and anomaly detection are becoming increasingly prominent. However, the existing methods often face the challenge of accuracy and efficiency when dealing with large-scale and high-dimensional data. In order to detect abnormal power data accurately and efficiently, this paper proposes an automatic detection method of abnormal power data based on chaotic sequence. Using chaotic sequence to encrypt the original power data increases the randomness and uncertainty of the data and improves the security of the data. The encrypted data are processed and clustered to extract the abnormal features of power data. Through cluster analysis, similar abnormal data patterns are grouped, and the similarity between abnormal data and normal data is calculated, so as to realize automatic detection of abnormal data. The experimental results show that this method is consistent with the actual situation, and the encryption effect is good, and the accuracy, precision and recall index are high. It is proved that this method is effective in automatic detection of abnormal power data in power system.