Articles | Volume 3, issue 2
https://doi.org/10.5194/wes-3-845-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-3-845-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Nov 2018
Research article |
| 05 Nov 2018
| 05 Nov 2018
Assessing variability of wind speed: comparison and validation of 27 methodologies
Joseph C. Y. Lee
CORRESPONDING AUTHOR
National Renewable Energy Laboratory, Golden, CO 80401, USA
Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, CO 80309, USA
M. Jason Fields
National Renewable Energy Laboratory, Golden, CO 80401, USA
Julie K. Lundquist
National Renewable Energy Laboratory, Golden, CO 80401, USA
Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, CO 80309, USA
Viewed
Total article views: 7,151 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 30 Jul 2018)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 5,507 | 1,542 | 102 | 7,151 | 90 | 79 |
- HTML: 5,507
- PDF: 1,542
- XML: 102
- Total: 7,151
- BibTeX: 90
- EndNote: 79
Total article views: 6,421 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 05 Nov 2018)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 5,102 | 1,226 | 93 | 6,421 | 79 | 70 |
- HTML: 5,102
- PDF: 1,226
- XML: 93
- Total: 6,421
- BibTeX: 79
- EndNote: 70
Total article views: 730 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 30 Jul 2018)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 405 | 316 | 9 | 730 | 11 | 9 |
- HTML: 405
- PDF: 316
- XML: 9
- Total: 730
- BibTeX: 11
- EndNote: 9
Viewed (geographical distribution)
Total article views: 7,151 (including HTML, PDF, and XML)
Thereof 5,733 with geography defined
and 1,418 with unknown origin.
Total article views: 6,421 (including HTML, PDF, and XML)
Thereof 5,050 with geography defined
and 1,371 with unknown origin.
Total article views: 730 (including HTML, PDF, and XML)
Thereof 683 with geography defined
and 47 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
18 citations as recorded by crossref.
- Contrasting hydrodynamic regimes of submerged pinnacle and emergent coral reefs G. Galbraith et al. 10.1371/journal.pone.0273092
- Exploiting offshore wind and solar resources in the Mediterranean using ERA5 reanalysis data T. Soukissian et al. 10.1016/j.enconman.2021.114092
- Analysis of short-term wind speed variation, trends and prediction: A case study of Tamil Nadu, India R. Kaja Bantha Navas et al. 10.1515/jisys-2023-0051
- Confidence Intervals for the Mean and Difference of Means of Birnbaum-Saunders Distributions with Application to Wind Speed Data N. Ratasukharom et al. 10.37394/23206.2024.23.54
- High-Resolution Wind Speed Estimates for the Eastern Mediterranean Basin: A Statistical Comparison Against Coastal Meteorological Observations S. Hadjipetrou & P. Kyriakidis 10.3390/wind4040016
- Inter Annual Variability of wind speed in India J. Bastin et al. 10.1080/01430750.2021.1945492
- Evaluating vector winds over eastern China in 2022 predicted by the CMA-MESO model and ECMWF forecast F. Huang et al. 10.1016/j.aosl.2024.100559
- Geophysical constraints on the reliability of solar and wind power worldwide D. Tong et al. 10.1038/s41467-021-26355-z
- Mitigation of offshore wind power intermittency by interconnection of production sites I. Solbrekke et al. 10.5194/wes-5-1663-2020
- Hybrid neurofuzzy investigation of short-term variability of wind resource in site suitability analysis: a case study in South Africa P. Adedeji et al. 10.1007/s00521-021-06001-x
- Future changes in wind energy potential over China using RegCM4 under RCP emission scenarios J. Wu et al. 10.1016/j.accre.2021.06.005
- Assessment of wind energy potential in Zambia G. Mwandila et al. 10.1016/j.esd.2024.101375
- Long-Term Assessment of Morocco’s Offshore Wind Energy Potential Using ERA5 and IFREMER Wind Data Y. Zekeik et al. 10.3390/jmse12030460
- How many offshore wind turbines does New England need? H. Livingston & J. Lundquist 10.1002/met.1969
- An overview of wind-energy-production prediction bias, losses, and uncertainties J. Lee & M. Fields 10.5194/wes-6-311-2021
- JRA55 is the best reanalysis representing observed near-surface wind speeds over India A. Das & S. Baidya Roy 10.1016/j.atmosres.2023.107111
- Wind power density characterization in arid and semi-arid Taita-Taveta and Garissa counties of Kenya I. Rotich & P. Musyimi 10.1016/j.clet.2023.100704
- Surface Wind Speed Changes and Their Potential Impact on Wind Energy Resources Across China During 1961–2021 X. Zhao et al. 10.1029/2023GH000861
17 citations as recorded by crossref.
- Contrasting hydrodynamic regimes of submerged pinnacle and emergent coral reefs G. Galbraith et al. 10.1371/journal.pone.0273092
- Exploiting offshore wind and solar resources in the Mediterranean using ERA5 reanalysis data T. Soukissian et al. 10.1016/j.enconman.2021.114092
- Analysis of short-term wind speed variation, trends and prediction: A case study of Tamil Nadu, India R. Kaja Bantha Navas et al. 10.1515/jisys-2023-0051
- Confidence Intervals for the Mean and Difference of Means of Birnbaum-Saunders Distributions with Application to Wind Speed Data N. Ratasukharom et al. 10.37394/23206.2024.23.54
- High-Resolution Wind Speed Estimates for the Eastern Mediterranean Basin: A Statistical Comparison Against Coastal Meteorological Observations S. Hadjipetrou & P. Kyriakidis 10.3390/wind4040016
- Inter Annual Variability of wind speed in India J. Bastin et al. 10.1080/01430750.2021.1945492
- Evaluating vector winds over eastern China in 2022 predicted by the CMA-MESO model and ECMWF forecast F. Huang et al. 10.1016/j.aosl.2024.100559
- Geophysical constraints on the reliability of solar and wind power worldwide D. Tong et al. 10.1038/s41467-021-26355-z
- Mitigation of offshore wind power intermittency by interconnection of production sites I. Solbrekke et al. 10.5194/wes-5-1663-2020
- Hybrid neurofuzzy investigation of short-term variability of wind resource in site suitability analysis: a case study in South Africa P. Adedeji et al. 10.1007/s00521-021-06001-x
- Future changes in wind energy potential over China using RegCM4 under RCP emission scenarios J. Wu et al. 10.1016/j.accre.2021.06.005
- Assessment of wind energy potential in Zambia G. Mwandila et al. 10.1016/j.esd.2024.101375
- Long-Term Assessment of Morocco’s Offshore Wind Energy Potential Using ERA5 and IFREMER Wind Data Y. Zekeik et al. 10.3390/jmse12030460
- How many offshore wind turbines does New England need? H. Livingston & J. Lundquist 10.1002/met.1969
- An overview of wind-energy-production prediction bias, losses, and uncertainties J. Lee & M. Fields 10.5194/wes-6-311-2021
- JRA55 is the best reanalysis representing observed near-surface wind speeds over India A. Das & S. Baidya Roy 10.1016/j.atmosres.2023.107111
- Wind power density characterization in arid and semi-arid Taita-Taveta and Garissa counties of Kenya I. Rotich & P. Musyimi 10.1016/j.clet.2023.100704
1 citations as recorded by crossref.
Latest update: 14 Nov 2024
Short summary
To find the ideal way to quantify long-term wind-speed variability, we compare 27 metrics using 37 years of wind and energy data. We conclude that the robust coefficient of variation can effectively assess and correlate wind-speed and energy-production variabilities. We derive adequate results via monthly mean data, whereas uncertainty arises in interannual variability calculations. We find that reliable estimates of wind-speed variability require 10 ± 3 years of monthly mean wind data.
To find the ideal way to quantify long-term wind-speed variability, we compare 27 metrics using...
Altmetrics
Final-revised paper
Preprint