An Efficient Dynamic State Estimation Algorithm including Bad Data Processing

This paper presents a comparison between the performance of dynamic and tracking estimators, in power systems operating under quasi-static conditions, concerning their characteristics of forecasting and filtering. From this comparison a new dynamic estimator which incorporates the main advantages of the previous estimators is proposed. Also, a new scheme of detection and identification of bad data properly built for dynamic algorithms is presented. Numerical results showing the performance of the new algorithm under different operational conditions are discussed.