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

Research Group in Smart Electrical Networks (GIREI)

Research output: Contribution to journal › Article › peer-review

21 Scopus citations

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.

Original language	English
Article number	e03559
Pages (from-to)	e03559
Journal	Heliyon
Volume	6
Issue number	3
DOIs	https://doi.org/10.1016/j.heliyon.2020.e03559
State	Published - Mar 2020

Keywords

ARX
Energy
Identification
Microgrid
No-linear systems
Petri net
State space model

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10.1016/j.heliyon.2020.e03559

Cite this

@article{fd1bcfcc848f4824be4ead81507dc06f,

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.",

keywords = "ARX, Energy, Identification, Microgrid, No-linear systems, Petri net, State space model",

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

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year = "2020",

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doi = "10.1016/j.heliyon.2020.e03559",

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T1 - A novel strategy for dynamic identification in AC/DC microgrids based on ARX and Petri Nets

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.

KW - ARX

KW - Energy

KW - Identification

KW - Microgrid

KW - No-linear systems

KW - Petri net

KW - State space model

UR - https://www.scopus.com/pages/publications/85082428974

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SN - 2405-8440

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SP - e03559

JO - Heliyon

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ER -

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

Abstract

Keywords

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Dynamic Identification and Fault Tolerance in Isolated AC/DC Hybrid Microgrids Using Multiple Strategies

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

Abstract

Keywords

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Dynamic Identification and Fault Tolerance in Isolated AC/DC Hybrid Microgrids Using Multiple Strategies

Cite this