Innovative use of phasor measurements in state estimation and parameter error identification

State Estimation plays a significant role in power systems secure operation. It performs real time monitoring of the entire system and provides the system states to other security applications. Recently, the Phasor Measurement Units (PMUs) have been invented and deployed to power systems to provide both phasor magnitudes and phase angles. This research focuses on enhancing power system state estimation and parameter error identification through innovative use of phasor measurements.;The first part of the dissertation focuses on improving network parameter error identification through innovative use of phasor measurements. Previous work has shown that the parameter errors in certain topologies could not be detected or identified without incorporating phasor measurements. This dissertation firstly investigates a computationally efficient algorithm to identify all such topologies for a given system. Then a strategic phasor measurement placement is proposed to ensure detectability and identifiability of certain network parameter errors. In addition, this method is reformulated and extended to detect and identify isolated power islands after disturbances.;Another way to improve parameter error identification is to use multiple measurement scans instead of the normal single measurement scan. This dissertation investigates an alternative approach using multiple measurement scans. It addresses limitations for parameter error in certain topologies without investing new measurements.;The second part of the dissertation concentrates on interoperability of PMUs in state estimation. Incorporating phasor measurements into existing Weighted Least Squares (WLS) state estimation brings up the interoperability issue about how to choose the right measurement weights for different types of PMUs. This part develops an auto tuning algorithm which requires no initial information about the phasor measurement accuracies. This algorithm is applied to tune the state estimator to update the weights of different types of PMUs in order to have a consistent numerically stable estimation solution. Furthermore, the impact of this tuning method on bad measurement detection is investigated.;All these methods have been tested in IEEE standard systems to show their performance.