Robust WLS estimator using reweighting techniques for electric energy systems

• A state estimator based on a weighted least squares model is proposed which is robust against outliers.
• The RWLS method considers measurement dependencies and its weights are automatically readjusted.
• Two realistic systems are studied and the results are analyzed using Design of Experiments and ANOVA techniques.

The state estimator is a key tool in the operation of any real-world electric energy system. In this paper, a state estimator based on a weighted least squares model is proposed which is robust against outliers. This algorithm presents two relevant features: robustness that is achieved by readjusting measurement weights, and accuracy that is attained by considering measurement dependencies. The proposed method is tested in the IEEE 57-bus and 118-bus systems and the obtained results are analyzed using Design of Experiments and ANOVA techniques.