Bad data processing for low voltage state estimation systems based on smart meter data

摘要

The area wide usage of smart meters in low voltage grids enables the identification of the three-phase system state with linear state estimation (SE) systems. In order to localize large measurement errors also bad data detection algorithms have to be applied. But as the measurement redundancy is typically small, the probability of bad data detection is usually small, too. This paper proposes a special three-phase SE approach which enables the reliable detection of bad data on the basis of the well-known normalized residuals method. In contrast to other algorithms active and reactive currents as well as absolute current values are used as input data for a linear SE system. Despite the simplicity of the process the results gathered from simulations and a field test are promising, showing appropriate bad data detection probabilities especially for voltage and active current bad data.