Optimal Load Modal Parameters Using Particle Swarm Optimization

Dynamic load models are of growing importance to the studies of power system dynamic analysis. However, the efficiency of such a model depends on the accuracy of model's parameter set. We propose a relatively new approach called particle swarm optimization (PSO), which has already been applied in various other fields and has been reported to show effective and efficient performance, to estimate the model's parameter set. The model parameter set is estimated by PSO, where the objective function to be minimized is the squared-error function between the simulating and experimental data. Tests of air conditioner response to voltage sags are documented. Significant improvements in simulation accuracy are demonstrated.

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