  This paper proposes a novel purely measurement-based method for estimating
dynamic load parameters in near real-time when stochastic load fluctuations are
present. By leveraging on the regression theorem for the Ornstein-Uhlenbeck
process, the proposed method can provide highly accurate estimation without
requiring any information about the power system model. Furthermore, by
exploiting recursion, an online algorithm is developed to estimate the dynamic
load parameters in near real-time. Simulation studies on the IEEE 39-Bus system
demonstrate the accuracy of the model-free method, its robustness against
measurement noise, as well as its satisfactory performance in tracking
real-time changes of the load parameters.
