Robust Event Detection using Synchrophasor Assisted Forecasting-Aided State Estimation

Identification of various power system events such as fault and power swing is important for its reliable and secure operation. Multiple sequential events may make the event identification algorithm complex. By taking advantage of The high reporting rate of Phasor Measurement Units (PMUs), this paper proposes a method to identify the power system events in the network. Synchronized voltage and current phasor measurements are utilized along with the forecasting-aided state estimator to extract the features of the event. The proposed method can detect an invalid PMU data and can correct it to avoid wrong identification of an event. The method is capable of detecting events like fault and power swing. The proposed event detection algorithm is validated on WSCC 9-bus system using the Real Time Digital Simulator (RTDS).