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

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Resumen

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.

Idioma originalInglés
Título de la publicación alojada6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022
EditoresDavid Rivas Lalaleo, Monica Karel Huerta
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781665487443
DOI
EstadoPublicada - 2022
Evento6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022 - Quito, Ecuador
Duración: 11 oct. 202214 oct. 2022

Serie de la publicación

Nombre6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022

Conferencia

Conferencia6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022
País/TerritorioEcuador
CiudadQuito
Período11/10/2214/10/22

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© 2022 IEEE.

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