A 34-year simulation of wind generation potential for Ireland and the impact of large-scale atmospheric pressure patterns
To study climate-related aspects of power system operation with large volumes of wind generation, data with sufficiently wide temporal and spatial scope are required. The relative youth of the wind industry means that long-term data from real systems are not available. Here, a detailed aggregated wi...
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ftunivcolldublin:oai:researchrepository.ucd.ie:10197/8402 2023-05-15T17:30:33+02:00 A 34-year simulation of wind generation potential for Ireland and the impact of large-scale atmospheric pressure patterns Cradden, Lucy C. McDermott, Frank Zubiate, Laura Sweeney, Conor O'Malley, Mark 2017-03-28T14:49:43Z http://hdl.handle.net/10197/8402 https://doi.org/10.1016/j.renene.2016.12.079 en eng Elsevier Renewable Energy http://hdl.handle.net/10197/8402 106 165 176 doi:10.1016/j.renene.2016.12.079 This is the author’s version of a work that was accepted for publication in Renewable Energy. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Renewable Energy (VOL 106, ISSUE 2017, (2017)) DOI:10.1016/j.renene.2016.12.079. Wind power MERRA reanalysis North Atlantic Oscillation East Atlantic Pattern Journal Article 2017 ftunivcolldublin https://doi.org/10.1016/j.renene.2016.12.079 2022-04-08T14:19:01Z To study climate-related aspects of power system operation with large volumes of wind generation, data with sufficiently wide temporal and spatial scope are required. The relative youth of the wind industry means that long-term data from real systems are not available. Here, a detailed aggregated wind power generation model is developed for the Republic of Ireland using MERRA reanalysis wind speed data and verified against measured wind production data for the period 2001–2014. The model is most successful in representing aggregate power output in the middle years of this period, after the total installed capacity had reached around 500 MW. Variability on scales of greater than 6 h is captured well by the model; one additional higher resolution wind dataset was found to improve the representation of higher frequency variability. Finally, the model is used to hindcast hypothetical aggregate wind production over the 34-year period 1980–2013, based on existing installed wind capacity. A relationship is found between several of the production characteristics, including capacity factor, ramping and persistence, and two large-scale atmospheric patterns – the North Atlantic Oscillation and the East Atlantic Pattern. Science Foundation Ireland University College Dublin Marie Skłodowska-Curie FP7-PEOPLE-2013-COFUND Article in Journal/Newspaper North Atlantic North Atlantic oscillation University College Dublin: Research Repository UCD Merra ENVELOPE(12.615,12.615,65.816,65.816) Renewable Energy 106 165 176 |
institution |
Open Polar |
collection |
University College Dublin: Research Repository UCD |
op_collection_id |
ftunivcolldublin |
language |
English |
topic |
Wind power MERRA reanalysis North Atlantic Oscillation East Atlantic Pattern |
spellingShingle |
Wind power MERRA reanalysis North Atlantic Oscillation East Atlantic Pattern Cradden, Lucy C. McDermott, Frank Zubiate, Laura Sweeney, Conor O'Malley, Mark A 34-year simulation of wind generation potential for Ireland and the impact of large-scale atmospheric pressure patterns |
topic_facet |
Wind power MERRA reanalysis North Atlantic Oscillation East Atlantic Pattern |
description |
To study climate-related aspects of power system operation with large volumes of wind generation, data with sufficiently wide temporal and spatial scope are required. The relative youth of the wind industry means that long-term data from real systems are not available. Here, a detailed aggregated wind power generation model is developed for the Republic of Ireland using MERRA reanalysis wind speed data and verified against measured wind production data for the period 2001–2014. The model is most successful in representing aggregate power output in the middle years of this period, after the total installed capacity had reached around 500 MW. Variability on scales of greater than 6 h is captured well by the model; one additional higher resolution wind dataset was found to improve the representation of higher frequency variability. Finally, the model is used to hindcast hypothetical aggregate wind production over the 34-year period 1980–2013, based on existing installed wind capacity. A relationship is found between several of the production characteristics, including capacity factor, ramping and persistence, and two large-scale atmospheric patterns – the North Atlantic Oscillation and the East Atlantic Pattern. Science Foundation Ireland University College Dublin Marie Skłodowska-Curie FP7-PEOPLE-2013-COFUND |
format |
Article in Journal/Newspaper |
author |
Cradden, Lucy C. McDermott, Frank Zubiate, Laura Sweeney, Conor O'Malley, Mark |
author_facet |
Cradden, Lucy C. McDermott, Frank Zubiate, Laura Sweeney, Conor O'Malley, Mark |
author_sort |
Cradden, Lucy C. |
title |
A 34-year simulation of wind generation potential for Ireland and the impact of large-scale atmospheric pressure patterns |
title_short |
A 34-year simulation of wind generation potential for Ireland and the impact of large-scale atmospheric pressure patterns |
title_full |
A 34-year simulation of wind generation potential for Ireland and the impact of large-scale atmospheric pressure patterns |
title_fullStr |
A 34-year simulation of wind generation potential for Ireland and the impact of large-scale atmospheric pressure patterns |
title_full_unstemmed |
A 34-year simulation of wind generation potential for Ireland and the impact of large-scale atmospheric pressure patterns |
title_sort |
34-year simulation of wind generation potential for ireland and the impact of large-scale atmospheric pressure patterns |
publisher |
Elsevier |
publishDate |
2017 |
url |
http://hdl.handle.net/10197/8402 https://doi.org/10.1016/j.renene.2016.12.079 |
long_lat |
ENVELOPE(12.615,12.615,65.816,65.816) |
geographic |
Merra |
geographic_facet |
Merra |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_relation |
Renewable Energy http://hdl.handle.net/10197/8402 106 165 176 doi:10.1016/j.renene.2016.12.079 |
op_rights |
This is the author’s version of a work that was accepted for publication in Renewable Energy. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Renewable Energy (VOL 106, ISSUE 2017, (2017)) DOI:10.1016/j.renene.2016.12.079. |
op_doi |
https://doi.org/10.1016/j.renene.2016.12.079 |
container_title |
Renewable Energy |
container_volume |
106 |
container_start_page |
165 |
op_container_end_page |
176 |
_version_ |
1766127393403043840 |