A novel strategy for dynamic identification in AC/DC microgrids based on ARX and Petri Nets

• Main Authors: Leony Ortiz, Luis B. Gutiérrez, Jorge W. González, Alexander Águila
• Format: Article
• Language: English
• Published: Elsevier 2020-03-01
• Series: Heliyon
• Subjects: Energy; Identification; Microgrid; No-linear systems; Petri net; State space model
• Online Access: http://www.sciencedirect.com/science/article/pii/S2405844020304047

This paper presents a new hybrid strategy which allows the dynamic identification of AC/DC microgrids (MG) by using algorithms such as Auto-Regressive with exogenous inputs (ARX) and Petri Nets (PN). The proposed strategy demonstrated in this study serves to obtain a dynamic model of the DC MG in isolated or connected modes. Given the non-linear nature of the system under study, the methodology divides the whole system in a bank of linearized models at different stable operating points, coordinated by a PN state machine. The bank of models obtained in state space, together with an adequate selection of models, can capture and reflect the non-linear dynamic properties of the AD/DC MGs and the different systems that it composes. The performance of the proposed algorithm has been tested using the Matlab/Simulink simulation platform.