Information debugging for real-time power systems monitoring

The authors present an efficient methodology for the detection, diagnosis and elimination of inconsistent data gathered during real-time power systems monitoring, using a dynamic state estimation algorithm. The capability of forecasting the system state and, consequently, the measurement set is the basic characteristic of the dynamic state estimators. Based on this characteristic a scheme for the detection of suspicious information is built. The suspicions are caused by: gross measurement errors, topological errors or gross forecasting errors due to sudden changes in the system operating point. The diagnosis about which type of error is actually present in the data set is carried out while taking into account the results of the forecasting and filtering steps of the state estimator. Numerical results of simulation studies with the proposed debugging algorithm are presented and discussed.<>