Real-Time Dynamic Parameter Estimation for an Exponential Dynamic Load Model

This paper is concerned about real-time modeling and identification of dynamically changing loads in power systems. An exponential dynamic load model was proposed earlier and was well accepted by several investigators who worked on this paper. This paper considers this model and identifies its parameters in real-time based on synchronously sampled measurements. An unscented Kalman filter is used to track the unknown parameters of the exponential dynamic load model. This paper first implements and tests the proposed method using simulated measurements. The method is then applied to actual recorded utility measurements to identify and track the bus load of the utility. The results are found to be promising, suggesting viability of tracking dynamic load models for online applications.