Analysis of Bad Data Processing Methodologies in Power System State Estimation

The reliability of results generated by state estimation are heavily impacted by measurement errors, topology errors, system transients and bad data injections. Detection and identification of such errors in a power system is important not only to monitor instrumentation performance but also to ensure system resilience. Despite their extensive application in power system state estimation research, the context and potency of WLS based bad data detection techniques is often overlooked. A better knowledge and implementation of such techniques will significantly improve the results by such work. This paper discusses the theoretical background and efficacy for the same. Results of simulation performed on a wide variety of systems to analyze the performance of each are presented.