Real time estimation of sensitive parameters of composite power system load model

Electric load modeling is of great importance in power system stability analysis and control. Composite load model including induction motor in parallel with static load has been widely accepted as an appropriate structure for describing load behaviors, especially for the studies that deal with power system stability. This paper proposes a nonlinear observer based on Extended Kalman Filter (EKF) to estimate the dominant parameters of the composite load model using real time measurements. The developed estimator can be implemented online and does not require a huge memory for recording load behavior data over a long time. The outcome of this paper makes the online dynamic stability analysis of power systems a step closer to reality. Simulation results are carried out to show the effectiveness of the proposed approach.