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

Energy

Volumn 114, Issue , 2016, Pages 1224-1239

  Staffell, Iain ^a   Pfenninger, Stefan ^b  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b ETH ZURICH   (Switzerland)

Author keywords

Capacity factor; Energy yield; Europe; Reanalysis; Wind farm; Wind power

Indexed keywords

NASA;

CAPACITY FACTORS; ENERGY YIELDS; EUROPE; REANALYSIS; WIND FARM;

WIND POWER;

CALIBRATION; CORRECTION; ENERGY RESOURCE; SIMULATION; TECHNOLOGICAL DEVELOPMENT; WIND FARM; WIND POWER;

ATLANTIC OCEAN; GERMANY; MEDITERRANEAN REGION; NORTH SEA; UNITED KINGDOM;

EID: 84985910644     PISSN: 03605442     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.energy.2016.08.068     Document Type: Article

References (58)

1. [1] Pierrot, M., The wind power database. 2015 URL: http://www.thewindpower.net.
2. [2] REN21, Renewables global status report. 2014 URL: http://www.ren21.net/gsr.
3. [3] ENTSO-E, Data portal > consumption data (hourly load values) and production data (detailed monthly production). 2015 URL: https://www.entsoe.eu/data/data-portal/consumption/.
4. [4] Sensfuß, F., Ragwitz, M., Genoese, M., The merit-order effect: a detailed analysis of the price effect of renewable electricity generation on spot market prices in Germany. Energy Policy 36:8 (2008), 3086–3094.
5. [5] Pöyry Energy Consulting, Implications of intermittency: Oxford. 2009 URL: http://www.uwig.org/ImpactofIntermittency.pdf.
6. [6] Green, R., Vasilakos, N., Storing wind for a rainy day: what kind of electricity does Denmark export?. Energy J 33:3 (2012), 1–22.
7. [7] UCTE, Final report: system disturbance on 4 November 2006. 2006 URL: http://tinyurl.com/6qtxq8v.
8. [8] Sinden, G., Characteristics of the UK wind resource: long-term patterns and relationship to electricity demand. Energy Policy 35:1 (2007), 112–127.
9. [9] Hughes, G., The performance of wind farms in the United Kingdom and Denmark. 2012, Renewable Energy Foundation, London URL: http://tinyurl.com/cn5qnqg.
10. [10] Staffell, I., Green, R., How does wind farm performance decline with age?. Renew Energy 66 (2014), 775–786.
11. [11] MacKay, D., On the performance of wind farms in the United Kingdom. 2013 URL: http://tinyurl.com/o4cj6ut.
12. [12] Staffell, I., Green, R., High quality wind data for energy systems models. Presented at energy systems conference. London, 2014 URL: http://tinyurl.com/hq-wind-data.
13. [13] Lu, X., McElroy, M.B., Kiviluoma, J., Global potential for wind-generated electricity. Proc Natl Acad Sci 106:27 (2009), 10933–10938.
14. [14] Cosseron, A., Gunturu, U.B., Schlosser, C.A., Characterization of the wind power resource in Europe and its intermittency. Energy Procedia 40:0 (2013), 58–66.
15. [15] Huber, M., Dimkova, D., Hamacher, T., Integration of wind and solar power in Europe: assessment of flexibility requirements. Energy 69:0 (2014), 236–246.
16. [16] Becker, S., Frew, B.A., Andresen, G.B., Zeyer, T., Schramm, S., Greiner, M., et al. Features of a fully renewable US electricity system: optimized mixes of wind and solar PV and transmission grid extensions. Energy 72:0 (2014), 443–458.
17. [17] McKenna, R., Hollnaicher, S., v. d. Leye, P Ostman, Fichtner, W., Cost-potentials for large onshore wind turbines in Europe. Energy 83:0 (2015), 217–229.
18. [18] Cannon, D.J., Brayshaw, D.J., Methven, J., Coker, P.J., Lenaghan, D., Using reanalysis data to quantify extreme wind power generation statistics: a 33 year case study in Great Britain. Renew Energy 75:0 (2015), 767–778.
19. [19] Drew, D.R., Cannon, D.J., Brayshaw, D.J., Barlow, J.F., Coker, P.J., The impact of future offshore wind farms on wind power generation in Great Britain. Resources 4:1 (2015), 155–171.
20. [20] Sharp, E., Dodds, P., Barrett, M., Spataru, C., Evaluating the accuracy of CFSR reanalysis hourly wind speed forecasts for the UK, using in situ measurements and geographical information. Renew Energy 77:0 (2015), 527–538.
21. [21] Andresen, G.B., Søndergaard, A.A., Greiner, M., Validation of Danish wind time series from a new global renewable energy atlas for energy system analysis. Energy 93 (2015), 1074–1088.
22. [22] Olauson, J., Bergkvist, M., Modelling the Swedish wind power production using MERRA reanalysis data. Renew Energy 76:0 (2015), 717–725.
23. [23] Staffell, I., Developing an open-access wind profile for Great Britain. 2014, Department of Energy & Climate Change, London.
24. [24] TradeWind, Integrating Wind: developing Europe's power market for the large-scale integration of wind power. 2009.
25. [25] Heide, D., von Bremen, L., Greiner, M., Hoffmann, C., Speckmann, M., Bofinger, S., Seasonal optimal mix of wind and solar power in a future, highly renewable Europe. Renew Energy 35:11 (2010), 2483–2489.
26. [26] Jacobson, M.Z., Delucchi, M.A., Providing all global energy with wind, water, and solar power, Part I: technologies, energy resources, quantities and areas of infrastructure, and materials. Energy Policy 39:3 (2011), 1154–1169.
27. [27] Kiss, P., Varga, L., Janosi, I.M., Comparison of wind power estimates from the ECMWF reanalyses with direct turbine measurements. J Renew Sustain Energy 1:3 (2009), 033105–033111.
28. [28] Kubik, M., Brayshaw, D.J., Coker, P.J., Barlow, J.F., Exploring the role of reanalysis data in simulating regional wind generation variability over Northern Ireland. Renew Energy 57 (2013), 558–561.
29. [29] Gunturu, U.B., Schlosser, C.A., Characterization of wind power resource in the United States. Atmos Chem Phys 12:20 (2012), 9687–9702.
30. [30] Hallgren, W., Gunturu, U.B., Schlosser, A., The potential wind power resource in Australia: a new perspective. PLoS One, 9(7), 2014, e99608.
31. [31] Ebisuzaki, W., Zhang, L., Reanalyes, best practices. Presented at 12th climate prediction applications science workshop (CPASW). Fairfax, VA, 2014.
32. [32] Slade, R., Bauen, A., Gross, R., Global bioenergy resources. Nat Clim Change 4:2 (2014), 99–105.
33. [33] Carbon Trust, Conversion factors. 2011 URL: https://www.carbontrust.com/media/18223/ctl153_conversion_factors.pdf.
34. [34] Berg, A.A., Famiglietti, J.S., Walker, J.P., Houser, P.R., Impact of bias correction to reanalysis products on simulations of North American soil moisture and hydrological fluxes. J Geophys Res Atmos 108:D16 (2003), 1–15.
35. [35] Stickler, A., Brönnimann, S., Significant bias of the NCEP/NCAR and twentieth-century reanalyses relative to pilot balloon observations over the West African Monsoon region (1940–1957). Q J R Meteorological Soc 137 (2011), 1400–1416.
36. [36] Decker, M., Brunke, M.A., Wang, Z., Sakaguchi, K., Zeng, X., Bosilovich, M.G., Evaluation of the reanalysis products from GSFC, NCEP, and ECMWF using flux tower observations. J Clim 25 (2012), 1916–1944.
37. [37] Christensen, J.H., Boberg, F., Christensen, O.B., Lucas-Picher, P., On the need for bias correction of regional climate change projections of temperature and precipitation. Geophys Res Lett, 35(20), 2008, L20709.
38. [38] Piani, C., Haerter, J.O., Coppola, E., Statistical bias correction for daily precipitation in regional climate models over Europe. Theor Appl Climatol 99:1–2 (2010), 187–192.
39. [39] Hagemann, S., Chen, C., Haerter, J.O., Heinke, J., Gerten, D., Piani, C., Impact of a statistical bias correction on the projected hydrological changes obtained from three GCMs and two hydrology models. J Hydrometeorol 12:4 (2011), 556–578.
40. [40] Hagemann, S., Haerter, J.O., Piani, C., Bias correction of climate model data – the golden solution for impact models or cursed black magic?. Presented at GCI conference. Bonn, 2010 URL: http://tinyurl.com/l5jtu2g.
41. [41] Ofgem, Electricity capacity assessment. Ref 126/12: London. 2012 URL: http://tinyurl.com/97cuuxt.
42. [42] Hawkins, S., Eager, D., Harrison, G.P., Characterising the reliability of production from future British offshore wind fleets. Presented at IET conference on renewable power generation (RPG 2011). Edinburgh, 2011.
43. [43] Kubik, M., Brayshaw, D., Coker, P., Reanalysis: an improved data set for simulating wind generation?. Presented at WREF 2012. Denver, CO, 2012 URL: http://tinyurl.com/c4ge72x.
44. [44] Rose, S., Apt, J., What can reanalysis data tell us about wind power?. Renew Energy 83 (2015), 963–969.
45. [45] Staffell, I., Green, R., Is there still merit in the merit order Stack? The impact of dynamic constraints on optimal plant mix. IEEE Trans Power Syst 31:1 (2016), 43–53.
46. [46] Rienecker, M.M., Suarez, M.J., Gelaro, R., Todling, R., Bacmeister, J., Liu, E., et al. MERRA: NASA's modern-era retrospective analysis for research and applications. J Clim 24:14 (2011), 3624–3648.
47. [47] Molod, A., Takacs, L., Suarez, M., Bacmeister, J., Development of the GEOS-5 atmospheric general circulation model: evolution from MERRA to MERRA2. Geosci Model Dev 8:5 (2015), 1339–1356.
48. [48] Liléo, S., Petrik, O., Investigation on the use of NCEP/NCAR, MERRA and NCEP/CFSR reanalysis data in wind resource analysis. Presented at EWEA. Brussels, Belgium, 2011 URL: http://proceedings.ewea.org/annual2011/papers/81.pdf.
49. [49] VTT, Wind energy statistics in Finland. 2015 URL: http://tinyurl.com/wind-energy-finland.
50. [50] Staffell, I., Using WindStats archives to assess the impact of cold climate on turbine output. Wind Rep 28:3 (2015), 1–3.
51. [51] European Commission, Eurostat database: electricity infrastructure (nrg_113a) and supply of renewable energies (nrg_107a). 2015 URL: http://ec.europa.eu/eurostat/data/database.
52. [52] EurObserv'ER, Wind energy barometer. 2015 URL: http://eurobserv-er.info/.
53. [53] BP, 64th statistical review of world energy. 2015 URL: http://bp.com/statisticalreview.
54. [54] ENTSO-E, Guidelines for monthly statistics data collection. 2015 URL: http://tinyurl.com/entsoe-ms-guidelines.
55. [55] Crabtree, C.J., Zappala, D., Hogg, S.I., Wind energy: UK experiences and offshore operational challenges. Proc IMechE, Part A J Power Energy 229:7 (2015), 727–746.
56. [56] DTU Wind Energy, Global wind atlas. 2016 URL: http://globalwindatlas.com/methods.html.
57. [57] Dee, D., Reanalysis at ECMWF. Presented at NOAA climate reanalysis task force technical workshop. College park, MD, 2015 URL: http://tinyurl.com/jbh24l9.
58. [58] Pfenninger, S., Staffell, I., Validated PV output simulations across Europe using reanalysis and satellite data. Energy, 2016, 10.1016/j.energy.2016.08.060.