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Development of a numerical modelling method to predict the seismic signals generated by wind farms

In efforts to reduce greenhouse gas emissions, renewable energies have been increasingly leveraged to generate power; in particular, the number of wind turbines has risen sharply in recent years and continues to grow. However, being mechanically coupled to the earth, wind turbines also generate grou...

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Autores principales: Limberger, Fabian, Rümpker, Georg, Lindenfeld, Michael, Deckert, Hagen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9478089/
https://www.ncbi.nlm.nih.gov/pubmed/36109555
http://dx.doi.org/10.1038/s41598-022-19799-w
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author Limberger, Fabian
Rümpker, Georg
Lindenfeld, Michael
Deckert, Hagen
author_facet Limberger, Fabian
Rümpker, Georg
Lindenfeld, Michael
Deckert, Hagen
author_sort Limberger, Fabian
collection PubMed
description In efforts to reduce greenhouse gas emissions, renewable energies have been increasingly leveraged to generate power; in particular, the number of wind turbines has risen sharply in recent years and continues to grow. However, being mechanically coupled to the earth, wind turbines also generate ground vibrations, which can have adverse effects on the capability of seismic observatories to detect and analyse earthquakes; nevertheless, the distances at which these signals modulate seismic records are disputed between the operators of wind farms and seismic observatories. Here, to quantify the noise signal amplitudes at distant seismometers, we develop the first numerical model to predict the seismic wavefield emitted by wind farms and simulate the complex effects of wavefield interferences, surface topography and attenuation. This modelling approach can reliably quantify the influences of multiple wind turbines on ground motion recordings and thus provide necessary information to aid decision-making in advance of wind farm installation.
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spelling pubmed-94780892022-09-17 Development of a numerical modelling method to predict the seismic signals generated by wind farms Limberger, Fabian Rümpker, Georg Lindenfeld, Michael Deckert, Hagen Sci Rep Article In efforts to reduce greenhouse gas emissions, renewable energies have been increasingly leveraged to generate power; in particular, the number of wind turbines has risen sharply in recent years and continues to grow. However, being mechanically coupled to the earth, wind turbines also generate ground vibrations, which can have adverse effects on the capability of seismic observatories to detect and analyse earthquakes; nevertheless, the distances at which these signals modulate seismic records are disputed between the operators of wind farms and seismic observatories. Here, to quantify the noise signal amplitudes at distant seismometers, we develop the first numerical model to predict the seismic wavefield emitted by wind farms and simulate the complex effects of wavefield interferences, surface topography and attenuation. This modelling approach can reliably quantify the influences of multiple wind turbines on ground motion recordings and thus provide necessary information to aid decision-making in advance of wind farm installation. Nature Publishing Group UK 2022-09-15 /pmc/articles/PMC9478089/ /pubmed/36109555 http://dx.doi.org/10.1038/s41598-022-19799-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Limberger, Fabian
Rümpker, Georg
Lindenfeld, Michael
Deckert, Hagen
Development of a numerical modelling method to predict the seismic signals generated by wind farms
title Development of a numerical modelling method to predict the seismic signals generated by wind farms
title_full Development of a numerical modelling method to predict the seismic signals generated by wind farms
title_fullStr Development of a numerical modelling method to predict the seismic signals generated by wind farms
title_full_unstemmed Development of a numerical modelling method to predict the seismic signals generated by wind farms
title_short Development of a numerical modelling method to predict the seismic signals generated by wind farms
title_sort development of a numerical modelling method to predict the seismic signals generated by wind farms
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9478089/
https://www.ncbi.nlm.nih.gov/pubmed/36109555
http://dx.doi.org/10.1038/s41598-022-19799-w
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