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Using bias-corrected reanalysis to simulate current and future wind power output

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  • Staffell, Iain
  • Pfenninger, Stefan

Abstract

Reanalysis models are rapidly gaining popularity for simulating wind power output due to their convenience and global coverage. However, they should only be relied upon once thoroughly proven. This paper reports the first international validation of reanalysis for wind energy, testing NASA's MERRA and MERRA-2 in 23 European countries. Both reanalyses suffer significant spatial bias, overestimating wind output by 50% in northwest Europe and underestimating by 30% in the Mediterranean. We derive national correction factors, and show that after calibration national hourly output can be modelled with R2 above 0.95. Our underlying data are made freely available to aid future research.

Suggested Citation

  • Staffell, Iain & Pfenninger, Stefan, 2016. "Using bias-corrected reanalysis to simulate current and future wind power output," Energy, Elsevier, vol. 114(C), pages 1224-1239.
  • Handle: RePEc:eee:energy:v:114:y:2016:i:c:p:1224-1239
    DOI: 10.1016/j.energy.2016.08.068
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    1. Richard Green and Nicholas Vasilakos, 2012. "Storing Wind for a Rainy Day: What Kind of Electricity Does Denmark Export?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    2. Raphael Slade & Ausilio Bauen & Robert Gross, 2014. "Global bioenergy resources," Nature Climate Change, Nature, vol. 4(2), pages 99-105, February.
    3. Heide, Dominik & von Bremen, Lueder & Greiner, Martin & Hoffmann, Clemens & Speckmann, Markus & Bofinger, Stefan, 2010. "Seasonal optimal mix of wind and solar power in a future, highly renewable Europe," Renewable Energy, Elsevier, vol. 35(11), pages 2483-2489.
    4. Jacobson, Mark Z. & Delucchi, Mark A., 2011. "Providing all global energy with wind, water, and solar power, Part I: Technologies, energy resources, quantities and areas of infrastructure, and materials," Energy Policy, Elsevier, vol. 39(3), pages 1154-1169, March.
    5. 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.
    6. 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.
    7. Huber, Matthias & Dimkova, Desislava & Hamacher, Thomas, 2014. "Integration of wind and solar power in Europe: Assessment of flexibility requirements," Energy, Elsevier, vol. 69(C), pages 236-246.
    8. Rose, Stephen & Apt, Jay, 2015. "What can reanalysis data tell us about wind power?," Renewable Energy, Elsevier, vol. 83(C), pages 963-969.
    9. 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.
    10. Cannon, D.J. & Brayshaw, D.J. & Methven, J. & Coker, P.J. & Lenaghan, D., 2015. "Using reanalysis data to quantify extreme wind power generation statistics: A 33 year case study in Great Britain," Renewable Energy, Elsevier, vol. 75(C), pages 767-778.
    11. Andresen, Gorm B. & Søndergaard, Anders A. & Greiner, Martin, 2015. "Validation of Danish wind time series from a new global renewable energy atlas for energy system analysis," Energy, Elsevier, vol. 93(P1), pages 1074-1088.
    12. Becker, Sarah & Frew, Bethany A. & Andresen, Gorm B. & Zeyer, Timo & Schramm, Stefan & Greiner, Martin & Jacobson, Mark Z., 2014. "Features of a fully renewable US electricity system: Optimized mixes of wind and solar PV and transmission grid extensions," Energy, Elsevier, vol. 72(C), pages 443-458.
    13. McKenna, R. & Hollnaicher, S. & Ostman v. d. Leye, P. & Fichtner, W., 2015. "Cost-potentials for large onshore wind turbines in Europe," Energy, Elsevier, vol. 83(C), pages 217-229.
    14. Olauson, Jon & Bergkvist, Mikael, 2015. "Modelling the Swedish wind power production using MERRA reanalysis data," Renewable Energy, Elsevier, vol. 76(C), pages 717-725.
    15. Sensfuß, Frank & Ragwitz, Mario & Genoese, Massimo, 2008. "The merit-order effect: A detailed analysis of the price effect of renewable electricity generation on spot market prices in Germany," Energy Policy, Elsevier, vol. 36(8), pages 3076-3084, August.
    16. 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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