Abstract
A novel method for detecting and identifying three fundamental anomalies, i.e. occurrence of bad data, changes in network configuration and sudden variation of states, in dynamic state estimation for electric power systems is proposed. Examination of innovation processes in the Kalman filter is appropriately used in each step of the detection of anomalies, discrimination between anomalies and application of counterplans. Discrimination between the anomalies is performed by a test based on skewness or the chi-square value of distributions of the innovation processes, although changes in network configuration and sudden variations of states are not always separable. Counterplans, which are different for each case of the anomalies, are developed so as to prevent deterioration in the accuracy of the estimator. Simulation results show that this algorithm works excellently.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEE Proceedings C Generation, Transmission and Distribution
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
