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Evaluating the accuracy of CFSR reanalysis hourly wind speed forecasts for the UK, using in situ measurements and geographical information

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  • Sharp, Ed
  • Dodds, Paul
  • Barrett, Mark
  • Spataru, Catalina

Abstract

Climate data can be used in simulations to estimate the output of wind turbines in locations where meteorological observations are not available. We perform the most comprehensive evaluation of the NCEP CFSR reanalysis model hourly wind speed hindcasts to date, and the first for the UK, by correlating the data against 264 onshore and 12 offshore synoptic weather stations, over a period of 30 years. The correlation of CFSR data to in situ measurements is similar to alternative approaches used in other studies both onshore and offshore. We investigate the impact of the topography, land use and mean wind speed on the onshore locations for the first time. The analysis of these spatial factors shows that CFSR represents the variety of terrain over UK well, and that the worst correlated sites are those at the highest elevations.

Suggested Citation

  • Sharp, Ed & Dodds, Paul & Barrett, Mark & Spataru, Catalina, 2015. "Evaluating the accuracy of CFSR reanalysis hourly wind speed forecasts for the UK, using in situ measurements and geographical information," Renewable Energy, Elsevier, vol. 77(C), pages 527-538.
    • Handle: RePEc:eee:renene:v:77:y:2015:i:c:p:527-538
    DOI: 10.1016/j.renene.2014.12.025
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    1. Green, Richard & Vasilakos, Nicholas, 2010. "Market behaviour with large amounts of intermittent generation," Energy Policy, Elsevier, vol. 38(7), pages 3211-3220, July.
    2. Kubik, M.L. & Brayshaw, D.J. & Coker, P.J. & Barlow, J.F., 2013. "Exploring the role of reanalysis data in simulating regional wind generation variability over Northern Ireland," Renewable Energy, Elsevier, vol. 57(C), pages 558-561.
    3. Sinden, Graham, 2007. "Characteristics of the UK wind resource: Long-term patterns and relationship to electricity demand," Energy Policy, Elsevier, vol. 35(1), pages 112-127, January.
    4. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2014. "WRF wind simulation and wind energy production estimates forced by different reanalyses: Comparison with observed data for Portugal," Applied Energy, Elsevier, vol. 117(C), pages 116-126.
    5. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2014. "Offshore wind energy resource simulation forced by different reanalyses: Comparison with observed data in the Iberian Peninsula," Applied Energy, Elsevier, vol. 134(C), pages 57-64.
    6. Staffell, Iain & Green, Richard, 2014. "How does wind farm performance decline with age?," Renewable Energy, Elsevier, vol. 66(C), pages 775-786.
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    Cited by:

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    24. Wang, Yi-Hui & Walter, Ryan K. & White, Crow & Farr, Hayley & Ruttenberg, Benjamin I., 2019. "Assessment of surface wind datasets for estimating offshore wind energy along the Central California Coast," Renewable Energy, Elsevier, vol. 133(C), pages 343-353.

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