Information geometry for model reduction of dynamic loads in power systems

Load modeling has been extensively studied in power systems. The problem is intrinsically hard, as a simple description is sought for a large collection of heterogeneous physical devices. One aspect of model simplification has to do with the number of parameters needed to describe a dynamic load. With the rich tapestry of methods proposed in the literature as a backdrop, this paper introduces a new approach to simplify the load models and estimate the parameters. Our method is based on information geometry which combines information theory with computational differential geometry to derive global estimation results and shed a new light on difficulties commonly encountered when fitting widely used models to the measurement data. The results are compared with the literature using simulations on the IEEE 14 bus benchmark system.