Power System Real-Time Operation Situation Assessment Based on Random Matrix Theory

The operation situation assessment is an important task in power systems, result of which can offer support on the safety analysis and control decision. With the deployments of phasor measurement units, massive amount of synchrophasor data is collected, which makes it possible for the real-time situational awareness of the entire system. In this paper, based on random matrix theory, a data-driven approach is proposed for real-time operation situation assessment in power systems. First, spatiotemporal data set is formulated by arranging high-dimensional synchrophasor measurements in chronological order. Based on the Ring Law in RMT for the empirical spectral analysis of `signal+noise' matrix, the mean spectral radius is introduced to indicate the system situation in macroscopic. The proposed approach is sensitive to the variation of the system situation and robust against random fluctuations and measurement errors. Cases on the synthetic data generated from IEEE 118-bus test system validate the effectiveness of the approach.