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Wind farm power optimization through wake steering

Global power production increasingly relies on wind farms to supply low-carbon energy. The recent Intergovernmental Panel on Climate Change (IPCC) Special Report predicted that renewable energy production must leap from [Formula: see text] of the global energy mix in 2018 to [Formula: see text] by 2...

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Autores principales: Howland, Michael F., Lele, Sanjiva K., Dabiri, John O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6642370/
https://www.ncbi.nlm.nih.gov/pubmed/31262816
http://dx.doi.org/10.1073/pnas.1903680116
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author Howland, Michael F.
Lele, Sanjiva K.
Dabiri, John O.
author_facet Howland, Michael F.
Lele, Sanjiva K.
Dabiri, John O.
author_sort Howland, Michael F.
collection PubMed
description Global power production increasingly relies on wind farms to supply low-carbon energy. The recent Intergovernmental Panel on Climate Change (IPCC) Special Report predicted that renewable energy production must leap from [Formula: see text] of the global energy mix in 2018 to [Formula: see text] by 2050 to keep global temperatures from rising 1.5°C above preindustrial levels. This increase requires reliable, low-cost energy production. However, wind turbines are often placed in close proximity within wind farms due to land and transmission line constraints, which results in wind farm efficiency degradation of up to [Formula: see text] for wind directions aligned with columns of turbines. To increase wind farm power production, we developed a wake steering control scheme. This approach maximizes the power of a wind farm through yaw misalignment that deflects wakes away from downstream turbines. Optimization was performed with site-specific analytic gradient ascent relying on historical operational data. The protocol was tested in an operational wind farm in Alberta, Canada, resulting in statistically significant ([Formula: see text]) power increases of [Formula: see text] – [Formula: see text] for wind speeds near the site average and wind directions which occur during less than [Formula: see text] of nocturnal operation and [Formula: see text] – [Formula: see text] for low wind speeds in the same wind directions. Wake steering also decreased the variability in the power production of the wind farm by up to [Formula: see text]. Although the resulting gains in annual energy production were insignificant at this farm, these statistically significant wake steering results demonstrate the potential to increase the efficiency and predictability of power production through the reduction of wake losses.
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spelling pubmed-66423702019-07-25 Wind farm power optimization through wake steering Howland, Michael F. Lele, Sanjiva K. Dabiri, John O. Proc Natl Acad Sci U S A Physical Sciences Global power production increasingly relies on wind farms to supply low-carbon energy. The recent Intergovernmental Panel on Climate Change (IPCC) Special Report predicted that renewable energy production must leap from [Formula: see text] of the global energy mix in 2018 to [Formula: see text] by 2050 to keep global temperatures from rising 1.5°C above preindustrial levels. This increase requires reliable, low-cost energy production. However, wind turbines are often placed in close proximity within wind farms due to land and transmission line constraints, which results in wind farm efficiency degradation of up to [Formula: see text] for wind directions aligned with columns of turbines. To increase wind farm power production, we developed a wake steering control scheme. This approach maximizes the power of a wind farm through yaw misalignment that deflects wakes away from downstream turbines. Optimization was performed with site-specific analytic gradient ascent relying on historical operational data. The protocol was tested in an operational wind farm in Alberta, Canada, resulting in statistically significant ([Formula: see text]) power increases of [Formula: see text] – [Formula: see text] for wind speeds near the site average and wind directions which occur during less than [Formula: see text] of nocturnal operation and [Formula: see text] – [Formula: see text] for low wind speeds in the same wind directions. Wake steering also decreased the variability in the power production of the wind farm by up to [Formula: see text]. Although the resulting gains in annual energy production were insignificant at this farm, these statistically significant wake steering results demonstrate the potential to increase the efficiency and predictability of power production through the reduction of wake losses. National Academy of Sciences 2019-07-16 2019-07-01 /pmc/articles/PMC6642370/ /pubmed/31262816 http://dx.doi.org/10.1073/pnas.1903680116 Text en Copyright © 2019 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Physical Sciences
Howland, Michael F.
Lele, Sanjiva K.
Dabiri, John O.
Wind farm power optimization through wake steering
title Wind farm power optimization through wake steering
title_full Wind farm power optimization through wake steering
title_fullStr Wind farm power optimization through wake steering
title_full_unstemmed Wind farm power optimization through wake steering
title_short Wind farm power optimization through wake steering
title_sort wind farm power optimization through wake steering
topic Physical Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6642370/
https://www.ncbi.nlm.nih.gov/pubmed/31262816
http://dx.doi.org/10.1073/pnas.1903680116
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