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Optimization of doubly-fed induction generator (DFIG)based wind turbine to achieve maximum power generation with imperialist competitive algorithm (ICA)
Today, due to the end of fossil fuels and efforts to reduce the use of renewable resources, wind energy is a suitable option for the production of electrical energy due to its high-power generation. To increase the output efficiency of wind turbines, maximum power point tracking techniques are requi...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10450475/ https://www.ncbi.nlm.nih.gov/pubmed/35833373 http://dx.doi.org/10.1177/00368504221113193 |
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author | Abdalkareem Jasim, Saade Mireya Romero Parra, Rosario Salam Karim, Yasir Mahdi, Ahmed B. Jade Catalan Opulencia, Maria Fakhriddinovich Uktamov, Khusniddin Thaeer Hammid, Ali |
author_facet | Abdalkareem Jasim, Saade Mireya Romero Parra, Rosario Salam Karim, Yasir Mahdi, Ahmed B. Jade Catalan Opulencia, Maria Fakhriddinovich Uktamov, Khusniddin Thaeer Hammid, Ali |
author_sort | Abdalkareem Jasim, Saade |
collection | PubMed |
description | Today, due to the end of fossil fuels and efforts to reduce the use of renewable resources, wind energy is a suitable option for the production of electrical energy due to its high-power generation. To increase the output efficiency of wind turbines, maximum power point tracking techniques are required for wind turbine energy conversion systems. In this research, the maximum power point (MPPT) method for two-way fed wind turbine systems (DFIG) is presented. The performance of the induction generator is presented on both sides of the power and the values of this generator such as speed, torque, voltage, current and maximum power at the time of wind speed changes. The presented work is presented in two scenarios and the model is performed without the algorithm then, a maximum power point tracking method based on the Colonial Competition Algorithm (ICA) has been applied to estimate the power of the two power induction generators. According to the results, it can be said that in the scenario with the algorithm of generating electric power by the turbine, several times in the production state is 9 MW, which is the rate of the turbine's nominal power, while in another scenario, the power generated by the turbine is 85% of the power in the state with the algorithm. |
format | Online Article Text |
id | pubmed-10450475 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-104504752023-08-26 Optimization of doubly-fed induction generator (DFIG)based wind turbine to achieve maximum power generation with imperialist competitive algorithm (ICA) Abdalkareem Jasim, Saade Mireya Romero Parra, Rosario Salam Karim, Yasir Mahdi, Ahmed B. Jade Catalan Opulencia, Maria Fakhriddinovich Uktamov, Khusniddin Thaeer Hammid, Ali Sci Prog Low-carbon generation for the restoration of our ecosystems: technology, strategy, and policy Today, due to the end of fossil fuels and efforts to reduce the use of renewable resources, wind energy is a suitable option for the production of electrical energy due to its high-power generation. To increase the output efficiency of wind turbines, maximum power point tracking techniques are required for wind turbine energy conversion systems. In this research, the maximum power point (MPPT) method for two-way fed wind turbine systems (DFIG) is presented. The performance of the induction generator is presented on both sides of the power and the values of this generator such as speed, torque, voltage, current and maximum power at the time of wind speed changes. The presented work is presented in two scenarios and the model is performed without the algorithm then, a maximum power point tracking method based on the Colonial Competition Algorithm (ICA) has been applied to estimate the power of the two power induction generators. According to the results, it can be said that in the scenario with the algorithm of generating electric power by the turbine, several times in the production state is 9 MW, which is the rate of the turbine's nominal power, while in another scenario, the power generated by the turbine is 85% of the power in the state with the algorithm. SAGE Publications 2022-07-14 /pmc/articles/PMC10450475/ /pubmed/35833373 http://dx.doi.org/10.1177/00368504221113193 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Low-carbon generation for the restoration of our ecosystems: technology, strategy, and policy Abdalkareem Jasim, Saade Mireya Romero Parra, Rosario Salam Karim, Yasir Mahdi, Ahmed B. Jade Catalan Opulencia, Maria Fakhriddinovich Uktamov, Khusniddin Thaeer Hammid, Ali Optimization of doubly-fed induction generator (DFIG)based wind turbine to achieve maximum power generation with imperialist competitive algorithm (ICA) |
title | Optimization of doubly-fed induction generator (DFIG)based wind turbine to achieve maximum power generation with imperialist competitive algorithm (ICA) |
title_full | Optimization of doubly-fed induction generator (DFIG)based wind turbine to achieve maximum power generation with imperialist competitive algorithm (ICA) |
title_fullStr | Optimization of doubly-fed induction generator (DFIG)based wind turbine to achieve maximum power generation with imperialist competitive algorithm (ICA) |
title_full_unstemmed | Optimization of doubly-fed induction generator (DFIG)based wind turbine to achieve maximum power generation with imperialist competitive algorithm (ICA) |
title_short | Optimization of doubly-fed induction generator (DFIG)based wind turbine to achieve maximum power generation with imperialist competitive algorithm (ICA) |
title_sort | optimization of doubly-fed induction generator (dfig)based wind turbine to achieve maximum power generation with imperialist competitive algorithm (ica) |
topic | Low-carbon generation for the restoration of our ecosystems: technology, strategy, and policy |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10450475/ https://www.ncbi.nlm.nih.gov/pubmed/35833373 http://dx.doi.org/10.1177/00368504221113193 |
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