Robust Hybrid Linear State Estimator Utilizing SCADA and PMU Measurements

This paper intends to improve the accuracy of power system State Estimation (SE) by introducing a hybrid linear robust state estimator. To this end, automatic bad data rejection is accomplished through an M-estimator, i.e. Schweppe-type estimator with Huber loss function. The method Iteratively Reweighted Least Squares (IRLS) used maximize likelihood function in M-estimator. Leverage measurements are also treated simple yet effective formulation. run algorithm for real-world large-scale grids, cumbersome construction Jacobian matrix at each iteration avoided. In addition, convergence local minima faced Gauss-Newton not concern as proposed formulation no approximation. As observability and redundancy considerations mandate SE take advantage traditional SCADA along available PMU measurements, linearity guaranteed regardless whether PMU-only, SCADA-only or SCADA/PMU utilized. regard, covariance weights derived both types measurements. Thanks therefore swiftness algorithm, could be different systems few up thousands buses.