Ambient Signal Based Load Model Parameter Identification Using Optimization Method

Load modelling is a crucial part in modelling a power system. The complex, nonlinear and stochastic characteristics of power load increase the difficulty of modelling. In this paper, a new approach of ambient signal based load model parameter identification method is proposed to solve this problem. With the proposed method, load model parameter can be identified in any time regardless of the existence of fault. First, Z+M model is simplified to reduce the number of parameters to be identified. Then, parameters of Z+M model are identified with an optimization method, the objective function of which is calculated from WAMS measured power and voltage data. An iterative process is proposed to solve the problem of initial value sensitivity in optimization problems. Finally, the effectiveness of this identification method is validated through the simulation results on WSCC three machines nine nodes system under different operation situation including both small disturbance and large disturbance.