On the comparison between ensemble Kalman filter and Kalman filter for the dynamic harmonic state estimation in a hybrid microgrid

The management of micro grids requires the dynamic harmonic state estimation of the system in order to perform control strategies that optimize waveform distortions. In industrial context, AC and DC devices and sources coexist and, therefore, micro grids can be a hybrid combination of AC and DC power sections. Also for such hybrid AC/DC micro grids optimal control strategies that optimize waveform distortions are mandatory. In this paper, the comparison of two different methods for the dynamic harmonic state estimation of hybrid AC/DC micro grids is performed analyzing both theoretical and numerical aspects. In particular, the Kalman Filter- and Ensemble Kalman Filter-based dynamic harmonic state estimations are compared in terms of accuracy and computational efforts. The numerical applications were performed on a hybrid AC/DC μG proposed for an actual industrial facility in southern Italy.