An Hybrid Algorithm based NARX for Non-Linear Identification and modeling of an AC/DC Hybrid Microgrid simulation

The paper presents two strategies that allow the identification and data selection from a Distributed Generation source in an AC/DC Hybrid Microgrid Benchmark for a non-linear system using the Non-linear Autoregressive Exogenous Model algorithm. Two mathematical algorithms were developed to facilitate identification and selection through black-box bank models to achieve this purpose. The mathematical development model is simulated through the MATLAB/Simulink software based on input data such as magnitude and angle, output data such as voltage per unit and current, connected to an AC/DC Hybrid Microgrid. Through this identification study, it is proposed to improve the selection of data from a Hybrid Microgrid in a more precise way so that future researchers can develop automatic control systems which identify and select possible failures in generation sources.