An ARX-Petri Nets algorithm for Active Identification of an AC/DC Microgrid Simulation

Abstract

In this article, a new algorithm is developed for the identification of an AC/DC Microgrid (MG) using methods of “Auto-Regressive with eXogenous inputs (ARX)” and Petri Nets (PN). An algorithm is shown in order to obtain a model of Distributed Generation (DG) systems for a MG. This algorithm aims to obtain a bank of models in which each model is obtained through the identification of a different point of operation. This method facilitates the identification of dynamic non-linear systems associated with MG systems. During the development of this research, a bank of models for converter systems are obtained in state space which reflect the nonlinear dynamic properties of the systems and converters that compose an AC/DC MG.