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

Leony Ortiz; Luis B. Gutiérrez; Jorge W. González; Alexander Águila

doi:10.1016/j.heliyon.2020.e03559

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

Leony Ortiz
, Luis B. Gutiérrez
, Jorge W. González
, Alexander Águila

Grupo de Investigación en Redes Eléctricas Inteligentes (GIREI)

Producción científica: Contribución a una revista › Artículo › revisión exhaustiva

21 Citas (Scopus)

Resumen

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.

Idioma original	Inglés
Número de artículo	e03559
Páginas (desde-hasta)	e03559
Publicación	Heliyon
Volumen	6
N.º	3
DOI	https://doi.org/10.1016/j.heliyon.2020.e03559
Estado	Publicada - mar. 2020

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10.1016/j.heliyon.2020.e03559

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Identificación Dinámica y Tolerancia a Fallos en Microrredes Híbridas CA/CC Aisladas Usando Múltiples Estrategias
Garcia Torres, E. M. (Investigador Secundario), Aguila Tellez, A. (Estudiante Investigador), Ortiz Matos, L. (Investigador principal), Pavon Vallejos, W. D. (Investigador Secundario), Gaybor Alban, J. C. (Estudiante Investigador), Guachamin Bustillos, D. R. (Estudiante Investigador), Tipanluisa Sarchi, W. B. (Estudiante Investigador), Gomez Samaniego, M. A. (Estudiante Investigador), Paredes Miranda, C. D. (Estudiante Investigador), Perez Pazmiño, A. J. (Estudiante Investigador), Buestan Vera, J. C. (Estudiante Investigador), Jimenez Pazmiño, E. A. (Estudiante Investigador), Filian Chavez, E. L. (Estudiante Investigador), Chiliquinga Guanoluisa, W. A. (Estudiante Investigador), Crisanto Perrazo, L. A. (Estudiante Investigador), Mejia Miranda, C. A. (Estudiante Investigador), Moreno Manosalvas, D. F. (Estudiante Investigador), Romulo Lozano, R. A. (Estudiante Investigador), Urgiles Navarrete, F. A. (Estudiante Investigador) & Ramirez Velasco, B. E. (Estudiante Investigador)
3/04/20 → 3/04/21
Proyecto: Investigación y Desarrollo

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

abstract = "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.",

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author = "Leony Ortiz and Guti{\'e}rrez, \{Luis B.\} and Gonz{\'a}lez, \{Jorge W.\} and Alexander {\'A}guila",

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AU - Ortiz, Leony

AU - Gutiérrez, Luis B.

AU - González, Jorge W.

AU - Águila, Alexander

PY - 2020/3

Y1 - 2020/3

N2 - 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.

AB - 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.

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KW - Energy

KW - Identification

KW - Microgrid

KW - No-linear systems

KW - Petri net

KW - State space model

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

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Identificación Dinámica y Tolerancia a Fallos en Microrredes Híbridas CA/CC Aisladas Usando Múltiples Estrategias

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