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

Gaybor Julio; Ortiz Leony; Aguila Alexander; Pavon Wilson; Ruiz Milton

doi:10.1109/ETCM56276.2022.9935724

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

Gaybor Julio, Ortiz Leony, Aguila Alexander, Pavon Wilson, Ruiz Milton

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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.

Original language	English
Title of host publication	6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022
Editors	David Rivas Lalaleo, Monica Karel Huerta
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665487443
DOIs	https://doi.org/10.1109/ETCM56276.2022.9935724
State	Published - 2022
Event	6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022 - Quito, Ecuador Duration: 11 Oct 2022 → 14 Oct 2022

Publication series

Name	6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022

Conference

Conference	6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022
Country/Territory	Ecuador
City	Quito
Period	11/10/22 → 14/10/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

Distributed Generation
Microgrid
Neural Network
Non-linear Autoregressive Exogenous Model
Power Electronics
Renewable Energy Systems

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/ETCM56276.2022.9935724

Cite this

Julio, G., Leony, O., Alexander, A., Wilson, P., & Milton, R. (2022). An Hybrid Algorithm based NARX for Non-Linear Identification and modeling of an AC/DC Hybrid Microgrid simulation. In D. R. Lalaleo, & M. K. Huerta (Eds.), 6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022 (6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ETCM56276.2022.9935724

Julio, Gaybor ; Leony, Ortiz ; Alexander, Aguila et al. / An Hybrid Algorithm based NARX for Non-Linear Identification and modeling of an AC/DC Hybrid Microgrid simulation. 6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022. editor / David Rivas Lalaleo ; Monica Karel Huerta. Institute of Electrical and Electronics Engineers Inc., 2022. (6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022).

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

abstract = "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.",

keywords = "Distributed Generation, Microgrid, Neural Network, Non-linear Autoregressive Exogenous Model, Power Electronics, Renewable Energy Systems",

author = "Gaybor Julio and Ortiz Leony and Aguila Alexander and Pavon Wilson and Ruiz Milton",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022 ; Conference date: 11-10-2022 Through 14-10-2022",

year = "2022",

doi = "10.1109/ETCM56276.2022.9935724",

language = "English",

series = "6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Julio, G, Leony, O , Alexander, A , Wilson, P & Milton, R 2022, An Hybrid Algorithm based NARX for Non-Linear Identification and modeling of an AC/DC Hybrid Microgrid simulation. in DR Lalaleo & MK Huerta (eds), 6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022. 6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022, Institute of Electrical and Electronics Engineers Inc., 6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022, Quito, Ecuador, 11/10/22. https://doi.org/10.1109/ETCM56276.2022.9935724

An Hybrid Algorithm based NARX for Non-Linear Identification and modeling of an AC/DC Hybrid Microgrid simulation. / Julio, Gaybor; Leony, Ortiz ; Alexander, Aguila et al.
6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022. ed. / David Rivas Lalaleo; Monica Karel Huerta. Institute of Electrical and Electronics Engineers Inc., 2022. (6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - An Hybrid Algorithm based NARX for Non-Linear Identification and modeling of an AC/DC Hybrid Microgrid simulation

AU - Julio, Gaybor

AU - Leony, Ortiz

AU - Alexander, Aguila

AU - Wilson, Pavon

AU - Milton, Ruiz

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

KW - Distributed Generation

KW - Microgrid

KW - Neural Network

KW - Non-linear Autoregressive Exogenous Model

KW - Power Electronics

KW - Renewable Energy Systems

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M3 - Conference contribution

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BT - 6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022

A2 - Lalaleo, David Rivas

A2 - Huerta, Monica Karel

PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Julio G, Leony O , Alexander A , Wilson P , Milton R. An Hybrid Algorithm based NARX for Non-Linear Identification and modeling of an AC/DC Hybrid Microgrid simulation. In Lalaleo DR, Huerta MK, editors, 6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022. Institute of Electrical and Electronics Engineers Inc. 2022. (6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022). doi: 10.1109/ETCM56276.2022.9935724

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

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

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