The theory and algorithm of detecting and identifying measurement biases in power system state estimation

The theory and algorithm of the detection and identification of measurement biases are developed. A fast and efficient recursive measurement biases estimation identification method is proposed. A set of linearized recursive formulae are developed to recursively calculate measurement residual averages and their variance. Using this algorithm, the long list of suspicious data can be avoided and the computational speed can be increased greatly. This adds a new function of monitoring on the operation of measurement system to the real network state analysis application software in power system control center and can improve the quality of the state estimation and the ability to detect and identify the bad data