Power Grid State Assessment Method Based on RMT-PCA

With the establishment of WAMS (Wide Area Measurement System), the power grid has accumulated a lot of measurement data. This paper proposes a power grid state assessment method based on RMT – PCA (Random Matrix Theory - Principal Component Analysis) from the perspective of data-driven. The proposed RMT-PCA-based method can effectively identify abnormal events such as load change under the operation state of power grid by using existing measurement data of power grid. The case study is designed to verify the accuracy and effectiveness of the method proposed in this paper. At the same time, the method proposed in this paper can reduce the calculation time, compared with the commonly used MSR (Mean Spectral Radius) index.