A comparison of methodologies for monthly wind energy estimation

Wind Energy

Volumn 12, Issue 7, 2009, Pages 640-659

  Garcia Bustamante E ^a,b   Gonzalez Rouco J F ^b   Jimenez P A ^a,b   Navarro, J ^a   Montavez J P ^c  

^a CIEMAT   (Spain)

^b UNIVERSIDAD COMPLUTENSE DE MADRID   (Spain)

^c UNIVERSITY OF MURCIA   (Spain)

Author keywords

Linearity; Power curve; Wind energy estimation; Wind speed

Indexed keywords

SPEED; WIND;

ENERGY ESTIMATION; FREQUENCY DISTRIBUTIONS; LINEARITY; POWER CURVES; SIMPLE LINEAR REGRESSION; STANDARD PROCEDURES; WIND POWER PRODUCTION; WIND SPEED;

WIND POWER;

ERROR ANALYSIS; ESTIMATION METHOD; LINEARITY; TEMPORAL ANALYSIS; TIMESCALE; WIND POWER; WIND VELOCITY;

EURASIA; EUROPE; SOUTHERN EUROPE; SPAIN;

EID: 70350703280     PISSN: 10954244     EISSN: 10991824     Source Type: Journal    
DOI: 10.1002/we.315     Document Type: Article

References (51)

1. Kariniotakis G, Pinson P, Siebert N, Giebel G, Barthelmie R. The state of the art in short-term prediction of wind power-from an offshore perspective. Proceedings of 2004 SeaTech Week 18-22 October 2004: Brest, France.
2. Weisser D, Foxon TJ. Implications of seasonal and diurnal variations of wind velocity for power output estimation of a turbine: a case study of Grenada. International Journal of Energy Research 2003; 27: 1165-1179.
3. Palutikof JP, Davies PM, Davies TD, Halliday JA. Impacts of spatial and temporal windspeed variability on wind energy output. Journal of Climate and Applied Meteorology 1987; 26: 1124-1133.
4. Jamil M, Parsa S, Majidi M. Wind power statistics and an evaluation of wind energy density. Renewable Energy 1995; 6: 623-628.
5. García A, Torres JL, Prieto E, de Francisco A. Fitting wind speed distributions: a case study. Solar Energy 1998; 62: 139-144.
6. Mathew S, Pandey KP, Kumar A. Analysis of wind regimes for energy estimation. Renewable Energy 2002; 25: 381-399.
7. Chang TJ, Wu YT, Hsu HY, Chu CR, Liao CM. Assessment of wind characteristics and wind turbine characteristics in Taiwan. Renewable Energy 2003; 28: 851-871.
8. Bechrakis DA, Deane JP, McKeogh EJ. Wind resource assessment of an area using short term data correlated to a long term data set. Solar Energy 2004; 76: 725-732.
9. Mengelkamp HT. Wind climate simulation over complex terrain and wind turbine energy output estimation. Theoretical and Applied Climatology 1999; 63: 129-139.
10. De Rooy W, Kok K. A combined physical-statistical approach for the down-scaling of model wind speed. Weather and Forecasting 2004; 19: 485-495.
11. Pryor SC, Barthelmie, R. Long-term trends in near-surface flow over the Baltic. International Journal of Climatology 2003; 23: 271-289.
12. Pryor SC, Barthelmie RJ, Schoof JT. Inter-annual variability of wind indices across Europe. Wind Energy 2006; 9: 27-38.
13. Balouktsis A, Chassapis D, Karapantsios T. A nomogram method for estimating the energy produced by wind turbine generators. Solar Energy 2002; 72: 251-259.
14. Weisser D. A wind energy analysis of Grenada: an estimation using the Weibull density function. Renewable Energy 2003; 28: 1803-1812.
15. Celik AN. Weibull representative compressed wind speed data for energy and performance calculations of wind energy systems. Renewable Energy 2003; 44: 3057-3072.
16. Li M, Li X. MEP-type distribution function: a better alternative to Weibull function for wind speed distribution. Renewable Energy 2005; 30: 1221-1240.
17. Pryor SC, Schoof JT, Barthelmie R. Climate change impacts on wind speeds and wind energy density in northern Europe: empirical downscaling of multiple AOGCMs. Climate Research 2005; 29: 183-198.
18. Seguro JV, Lambert, TW. Modern estimation of the parameters of the Weibull wind speed distribution for wind energy analysis. Journal of Wind Engineering and Industrial Aerodynamics 2000; 85: 75-84.
19. Jaramillo OA, Borja MA. Wind speed analysis in La Ventosa, Mexico: a bimodal probability distribution case. Renewable Energy 2004; 29: 1613-1630.
20. Ackerman T, Soder L. An overview of wind energy-status 2002. Renewable and Sustainable Energy Reviews 2002; 6: 67-128.
21. Jager-Waldau A, Ossenbrink H. Progress of electricity from biomass, wind and photovoltaics in the European Union. Renewable and Sustainable Energy Reviews 2004; 8: 157-182.
22. Flowers LT, Dougherty PJ. Wind powering America: goals, approach perspectives and prospects. SAMPE Journals 2004; 40: 44-46.
23. Kenisarin M, Karsli VM, Caglar M. Wind power engineering in the world and perspectives of its development in Turkey. Renewable and Sustainable Energy Reviews 2006; 10: 341-369.
24. Faulin J, Lera F, Pintor JM, García J. The outlook for renewable energy in Navarre: an economic profile. Energy Policy 2006; 34: 2201-2216.
25. Fairless D. Renewable energy: energy-go-round. How did a little Spanish province become one of the world's windenergy giants? Nature 2007; 447: 1031-1142.
26. García-Bustamante E, González-Rouco JF, Jiménez PA, Navarro J and Montávez JP. The influence of the Weibull assumption in monthly wind energy estimation. Wind Energy 2008; 11: 483-502.
27. Celik AN. Energy output estimation for small-scale wind power generators using Weibull-representative wind data. Journal of Wind and Industrial Aerodynamics 2003; 91: 693-707.
28. Aubrun S, Koppman R, Leitl B, Mollman-Coers, Schaub A. Physical modelling of a complex forest area in a wind tunnel-comparison with field data. Agricultural and Forest Meteorology 2005; 129: 121-135.
29. Barthelmie RJ, Frandsen ST, Nielsen MN, Pryor SC, Rethore PE, Jorgensen HE. Modelling and measurements of power losses and turbulence intensity in wind turbine wakes at Middelgrunden offshore wind farm. Wind Energy 2007; 10: 517-528.
30. Jiménez PA, González-Rouco JF, Montávez JP, García-Bustamante E, Navarro J, Valero F. Surface wind regionalization in complex terrain. Journal of Applied Meteorology and Climatology 2008; 47: 308-325.
31. Jiménez PA, González-Rouco JF, Montávez JP, García-Bustamante E, Navarro J. Climatology of wind patterns in the Northeast of the Iberian Peninsula. International Journal of Climatology 2008: DOI: 10.1002/joc.1705.
32. Celik AN. Assessing the suitability of wind speed probability distribution functions on wind power density. Renewable Energy 2003; 28: 1563-1574.
33. Biswas S, Sraedhar BN, Singh YP. A simplified statistical technique for wind turbine energy output estimation. Wind Engineering 1990; 19: 147-155.
34. Celik AN. On the distributional parameters used in assessment of the suitability of wind speed probability density functions. Energy Conversion and Management 2004; 45: 1735-1747.
35. Pryor SC, Schoof JT, Barthelmie RJ. Empirical downscaling of wind speed probability distributions. Journal of Geophysical Research 2005; 110: D19109.
36. Tuller SE, Brett CA. The characteristics of wind velocity that favor the fitting of a Weibull distribution in wind speed analysis. Journal of Climate and Applied Meteorology 1984; 23: 124-134.
37. Dorvlo ASS. Estimating wind speed distribution. Energy Conversion and Management 2002; 43: 2311-2318.
38. Noorgard P, Holttinen H. A Multi-Turbine Power Curve Approach. Nordic Wind Power Conference, Chalmers University of Technology, 2004.
39. Bivona S, Burlon R, Leone C. Hourly wind speed analysis in Sicily. Renewable Energy 2003; 28: 1371-1385.
40. von Storch H, Zwiers F. Statistical Analysis in Climate Research. Cambridge University Press: Cambridge, 1999.
41. Bergey KH. Lanchester-Betz limit. Journal of Energy 1979; 3: 382-384.
42. Kaas E, Li T-H, Schmith T. Statistical hindcast of wind climatology in the North Atlantic and northwestern European region. Climate Research 1996; 7: 97-110.
43. Conradsen K, Nielsen LB. Review of Weibull statistics for estimation of wind speed. Journal of Climate and Applied Meteorology 1984; 23: 1173-1183.
44. Vestas. General specifications 600 kW variable slip wind turbines. Vestas-American Wind Technology technical note 941615.R3 25 pp., 1996.
45. Pinson P, Nielsen HA, Moller JK, Madsen H, Kariniotakis GN. Nonparametric probabilistic forecasts of wind power: required properties and evaluation. Wind Energy 2007; 10: 497-516. (Pubitemid 350273129)
46. Pinson P, Nielsen H Aa, Madsen H, Nielsen TS. Local linear regression with adaptive orthogonal fitting for the wind power application. Statistics and Computing 2008; 18: 59-71.
47. Hwang-Dae K, Robinson TJ, Wulff SS, Parker PA. Comparison of parametric, nonparametric and semiparametric modeling of wind tunnel data. Quality Engineering 2007; 19: 179-190.
48. Caires S, Sterl A. A new nonparametric method to correct model data: application to significant wave height from the ERA-40 re-analysis. Journal of Atmospheric and Oceanic Technology 2005; 22: 443-459.
49. Lange M. On the uncertainty of wind power predictions: analysis of the forecast accuracy and statistical distribution of errors. Journal of Solar Energy Engineering 2005; 27: 177-184.
50. Lackner MA, Rogers AL, Manwell JF. Uncertainty analysis in MCP-based wind resource assessment and energy production estimation. Journal of Solar Energy Engineering 2008; 031006: 1-10.
51. Pryor SC, Barthelmie R, Kjellström E. Potential climate change impact on wind energy resources in northern Europe: analyses using a regional climate model. Climate Dynamics 2005; 25: 815-835.