Enhanced State Estimation by Advanced Substation Monitoring

This is a project report from the Power Systems Engineering Research Center (PSERC). PSERC is a multi-university Center conducting research on challenges facing a restructuring electric power industry and educating the next generation of power engineers. Notice Concerning Copyright Material PSERC members are given permission to copy without fee all or part of this publication for internal use if appropriate attribution is given to this document as the source material. This report is available for downloading from the PSERC website. Executive Summary Power system substations are becoming equipped with intelligent electronic devices (IEDs) that are primarily used for protection and relaying functions as well as for power quality monitoring. The advanced communication and computational capabilities provided by these devices can be exploited to improve energy management system (EMS) applications. This project is concerned about one such application: the monitoring of power systems during normal operating conditions. Conventional monitoring involves scanning the measurements from various substations in the system and estimating the system state using a state estimator at the EMS control center. While state estimators can detect and identify most types of analog measurement errors, they are still vulnerable to errors in system topology. These errors show up when the assumed status of circuit breakers and switches does not coincide with their true status. This project investigates solutions to the detection, identification and elimination of such errors via the help of substation IEDs. One of the reasons why certain topological errors go undetected is that some measurements at the substation level cannot be used by the state estimator. This is because the overall system model does not include the detailed representation of substation configurations. In this project, these redundant substation-level measurements are integrated into the state estimator to improve topology error identification, error rejection and statistical robustness features. Furthermore, other error sources that are not topological, such as errors due to phase imbalances, are analyzed to determine their influence on the state estimation results. This project's results suggest that processing measurements at the substation level before sending them to the control center can improve state estimator performance. In addition, availability of detailed substation measurements can facilitate topology error identification by the state estimator executed at the control-center level. These benefits are demonstrated under various operating scenarios using prototype software developed as part of the project.