A New Kalman Filter Approach Including System Frequency for an Effective PMU-based Power System State Estimation

This paper presents a new PMU-based Kalman Filter approach for Power System State Estimation, in which an estimator model is proposed to include the system frequency and exploit synchronized frequency measurements. The performance of this new estimator is evaluated in comparison to different state estimation methodologies, in order to assess the impact and potential benefits given by the integration of the frequency input. The improvement in the estimation accuracy achievable for the quantities of interest (node voltages and branch currents) thanks to the proposed approach is assessed under realistic operating conditions, taking into account, in particular, the possible occurrence of off-nominal frequency conditions. The main findings and results obtained by means of simulations performed on a standard IEEE network are presented and discussed.