Abnormity handing for power system adaptive dynamic state estimation

Based on supervisory control and data acquisition (SCADA) system, an efficient method for detection, identification and elimination of abnormality during power system adaptive dynamic state estimation is proposed in this paper. In this method, according to the capability of predicting the system state of the adaptive dynamic state estimator, the suspicions that the new method deals with include: multi bad data, sudden load change, network topology error and the simultaneity of the three anomalies on the system states. Simulation results show that the presented debugging algorithm has good performance in detecting, diagnosing and processing various anomalies.