Power system dynamic load modeling using artificial neural networks

The dynamic characteristics of power system loads are critical to obtaining quality operating point-prediction and stability calculations. The composition of components at a load bus makes the aggregated behavior too complicated to be expressed by a simple form. Armed with the theorems recently developed on the approximation capability of artificial neural networks, the authors devise a load model to describe the complex dynamic behavior of loads. Real field data are used to train and test this model. The results verify that this model can emulate load dynamics well and should therefore be suitable as a representation of load for stability analysis