Novel algorithms to estimate and adaptively update measurement error variance using power system state estimation results

This paper presents novel algorithms for on-line estimating and adaptively updating measurement error variance by using power system state estimation results. The idea hinges on the relationship between the residual variance and measurement error variance. The residual variance is estimated with the residual sample variance and the measurement error variance is then obtained by solving the residual sample variance equation. The statistical properties of the sample variance are discussed. The relation between the estimation precision and sample size under given confidence levels is derived. The on-line estimation and adaptive updating of measurement error variance can provide the state estimator with more accurate weights to improve the quality of state estimation calculation and the ability to detect and identify bad data.