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 original | Inglés |
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Título de la publicación alojada | 6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022 |
Editores | David Rivas Lalaleo, Monica Karel Huerta |
Editorial | Institute of Electrical and Electronics Engineers Inc. |
ISBN (versión digital) | 9781665487443 |
DOI | |
Estado | Publicada - 2022 |
Evento | 6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022 - Quito, Ecuador Duración: 11 oct. 2022 → 14 oct. 2022 |
Serie de la publicación
Nombre | 6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022 |
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Conferencia
Conferencia | 6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022 |
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País/Territorio | Ecuador |
Ciudad | Quito |
Período | 11/10/22 → 14/10/22 |
Nota bibliográfica
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