A PMU Data Recovery Method Based on Feature Component Extraction
Zhiwei Yang, Hao Liu, Tianshu Bi, Qixun Yang, Ancheng Xue · 2019
Phasor Measurement Units (PMUs) have become the basic means of real-time monitoring and closed-loop control of power grids due to their synchronization, rapidity and accuracy. However, PMUs usually have different levels of data loss problems due to many factors, which seriously restricts its applications in the power systems. In this paper, a PMU data recovery method based on feature component extraction is proposed. First three types of data loss are summarized. Then the original signal is decomposed to extract all the components. And data is recovered by reconstructed signal with optimal components. The proposed method has been tested using artificial and field data. And the case studies verify that this method could realize a decent recovery for different types of data loss, which is of great significance and value for ensuring PMU data quality. This paper also reveals the interesting direction for future work.