Parameter Estimation of Dynamic Load Model in Power System by using Measured Data

Abstract

In this paper, we propose a dynamic load model considering change of flux inside induction motor for transient stability analysis and we present a new method for estimating unknown parameters of the dynamic load model. The model is a parallel composite of a constant impedance load and an induction motor load behind a series constant reactance. An adequate dynamic load model is essential for evaluating power system stability and this model can represent the behavior of actual load by using appropriate parameters. However, the problem of this model has a large amount of parameters and it is not easy to estimate a lot of unknown parameters. Therefore we propose an estimating method based on Particle Swarm Optimization (PSO), which is a non-linear optimization method, by using measured instantaneous voltage sag data. We estimated parameters of the actual load by PSO to minimize error between calculated and measured power of load after a load drop due to voltage sag by the accident. It was confirmed that the proposed method was successful and PSO is effective in parameter estimation.