Particle swarm optimization applied in power system measurement-based load modeling

An application of particle swarm optimization algorithm for power system measurement-based load modeling is presented in this paper. Load modeling based on measurements is formulated as an optimization problem, which minimizes the difference between the measured and the simulated response of a model. A composite load model is used as model structure and particle swarm optimization algorithm is used for parameter estimation of the load model. A modification to particle swarm optimization is applied to improve its performance. Tests were carried out on a modified IEEE 14-bus test system. The results show the capabilities of composite load model to represent the load behavior after disturbances, and also the capabilities of particle swarm optimization for obtaining adequate estimations of load parameters.