Automatic Bad Data Detection in State Estimation Using an optimization Model

In this paper an optimization model is proposed to detect the bad data in state estimation of power system. The proposed model detect, identify and remove the bad data from the estimation process simultaneously. A threshold for measurement reside is extracted using the Chi-squared test assuming the normal probability distribution function of measurement errors. The efficacy of the proposed method is investigated over the IEEE 118-bus test system under different types of bad data.