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Maximum power point tracking dataset for a wind energy conversion system based on a reverse-controller for a multilevel boost converter
The database here contains experimental data relevant to an original maximum power point tracking controller for an experimental direct-drive full-variable-speed full-rated converter Type IV Wind Energy Conversion System in standalone operation. The main goal is to maximize power extraction by contr...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8842028/ https://www.ncbi.nlm.nih.gov/pubmed/35198679 http://dx.doi.org/10.1016/j.dib.2022.107900 |
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author | González-Hernández, José Genaro Salas-Cabrera, Rubén Vázquez-Bautista, Roberto Ong-de-la-Cruz, Luis Manuel |
author_facet | González-Hernández, José Genaro Salas-Cabrera, Rubén Vázquez-Bautista, Roberto Ong-de-la-Cruz, Luis Manuel |
author_sort | González-Hernández, José Genaro |
collection | PubMed |
description | The database here contains experimental data relevant to an original maximum power point tracking controller for an experimental direct-drive full-variable-speed full-rated converter Type IV Wind Energy Conversion System in standalone operation. The main goal is to maximize power extraction by controlling the duty cycle of a multilevel boost converter, which is responsible for adjusting the angular speed of a permanent magnet synchronous generator coupled to a three-phase induction motor that emulates the wind turbine. Two data acquisition cards with the appropriate signal conditioners were used to obtain measurements of the generator angular speed, output current, and output voltage at the terminals of the multilevel converter. In addition, data related to power coefficient, tip speed ratio, duty cycle, and output power are also included. Two PCs in a Linux real-time platform were used for the emulation, control, and data collection processes. On the other hand, Matlab was used to analyze the data to evaluate the controller's performance to maximize wind power extraction. The database is freely accessible at http://dx.doi.org/10.17632/363d24mcb6.2. This dataset [1] represents a resource for wind power specialists who develop algorithms for wind energy optimization. |
format | Online Article Text |
id | pubmed-8842028 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-88420282022-02-22 Maximum power point tracking dataset for a wind energy conversion system based on a reverse-controller for a multilevel boost converter González-Hernández, José Genaro Salas-Cabrera, Rubén Vázquez-Bautista, Roberto Ong-de-la-Cruz, Luis Manuel Data Brief Data Article The database here contains experimental data relevant to an original maximum power point tracking controller for an experimental direct-drive full-variable-speed full-rated converter Type IV Wind Energy Conversion System in standalone operation. The main goal is to maximize power extraction by controlling the duty cycle of a multilevel boost converter, which is responsible for adjusting the angular speed of a permanent magnet synchronous generator coupled to a three-phase induction motor that emulates the wind turbine. Two data acquisition cards with the appropriate signal conditioners were used to obtain measurements of the generator angular speed, output current, and output voltage at the terminals of the multilevel converter. In addition, data related to power coefficient, tip speed ratio, duty cycle, and output power are also included. Two PCs in a Linux real-time platform were used for the emulation, control, and data collection processes. On the other hand, Matlab was used to analyze the data to evaluate the controller's performance to maximize wind power extraction. The database is freely accessible at http://dx.doi.org/10.17632/363d24mcb6.2. This dataset [1] represents a resource for wind power specialists who develop algorithms for wind energy optimization. Elsevier 2022-02-02 /pmc/articles/PMC8842028/ /pubmed/35198679 http://dx.doi.org/10.1016/j.dib.2022.107900 Text en © 2022 The Author(s). Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article González-Hernández, José Genaro Salas-Cabrera, Rubén Vázquez-Bautista, Roberto Ong-de-la-Cruz, Luis Manuel Maximum power point tracking dataset for a wind energy conversion system based on a reverse-controller for a multilevel boost converter |
title | Maximum power point tracking dataset for a wind energy conversion system based on a reverse-controller for a multilevel boost converter |
title_full | Maximum power point tracking dataset for a wind energy conversion system based on a reverse-controller for a multilevel boost converter |
title_fullStr | Maximum power point tracking dataset for a wind energy conversion system based on a reverse-controller for a multilevel boost converter |
title_full_unstemmed | Maximum power point tracking dataset for a wind energy conversion system based on a reverse-controller for a multilevel boost converter |
title_short | Maximum power point tracking dataset for a wind energy conversion system based on a reverse-controller for a multilevel boost converter |
title_sort | maximum power point tracking dataset for a wind energy conversion system based on a reverse-controller for a multilevel boost converter |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8842028/ https://www.ncbi.nlm.nih.gov/pubmed/35198679 http://dx.doi.org/10.1016/j.dib.2022.107900 |
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