Using machine learning to predict wind turbine power output

Environmental Research Letters

Volumn 8, Issue 2, 2013, Pages

  Clifton, A ^a   Kilcher, L ^a   Lundquist, J K ^a,b   Fleming, P ^a  

^a NATIONAL RENEWABLE ENERGY LABORATORY   (United States)

^b UNIVERSITY OF COLORADO   (United States)

Author keywords

classification and regression trees; machine learning; wind energy; wind turbine

Indexed keywords

ATMOSPHERIC THERMODYNAMICS; FORECASTING; FORESTRY; LEARNING SYSTEMS; REGRESSION ANALYSIS; THERMOELECTRIC POWER; TURBULENCE; WIND EFFECTS; WIND POWER; WIND TURBINES;

ATMOSPHERIC CONDITIONS; CLASSIFICATION AND REGRESSION TREE; REGRESSION TREE MODELS; TURBINE PERFORMANCE; TURBULENCE AND SHEARS; TURBULENCE INTENSITY; WIND RESOURCE ASSESSMENT; WIND TURBINE POWER;

TREES (MATHEMATICS);

ACCURACY ASSESSMENT; ARTIFICIAL INTELLIGENCE; EQUIPMENT COMPONENT; NUMERICAL MODEL; PERFORMANCE ASSESSMENT; PREDICTION; PRODUCTIVITY; REGRESSION ANALYSIS; RESOURCE ASSESSMENT; TURBULENCE; WIND POWER; WIND SHEAR; WIND TURBINE; WIND VELOCITY;

CLASSIFICATION; FORESTRY; MATHEMATICS; REGRESSION ANALYSIS; TREES; TURBULENCE;

EID: 84880911595     PISSN: None     EISSN: 17489326     Source Type: Journal    
DOI: 10.1088/1748-9326/8/2/024009     Document Type: Article

References (26)

1. Antoniou I, Pedersen S M and Enevoldsen P B 2009 Wind shear and uncertainties in power curve measurement and wind resources Wind Eng. 33 449-68
2. Barbounis T, Theocharis J, Alexiadis M and Dokopoulos P 2006 Long-term wind speed and power forecasting using local recurrent neural network models IEEE Trans. Energy Convers. 21 273-84
3. Breiman L, Friedman J, Olshen R and Stone C 1984 Classification and Regression Trees (Boca Raton, FL: CRC Press)
4. Brower M 2012 Wind Resource Assessment: A Practical Guide to Developing a Wind Project (New York: Wiley)
5. Clifton A and Lundquist J K 2012 Data clustering reveals climate impacts on local wind phenomena J. Appl. Meteorol. Climatol. 51 1547-57
6. Clifton A, Schreck S, Scott G, Kelley N D and Lundquist J 2012 Turbine inflow characterization at the National Wind Technology Center J. Sol. Energy Eng. accepted
7. Delle Monache L, Nipen T, Liu Y, Roux G and Stull R 2011 Kalman filter and analog schemes to postprocess numerical weather predictions Monthly Weather Rev. 139 3554-70
8. European Commission 2011 Renewables make the difference Tech. Rep. European Commission
9. Hedevang E 2012 Wind turbine power curves incorporating turbulence intensity Wind Energy at press (doi:10.1002/we.1566)
10. International Electrotechnical Commission 2005 IEC 61400-12: Wind Turbines - Part 12: Power Performance Measurements of Electricity Producing Wind Turbines 1st PPUB edn (Geneva, Switzerland: International Electrotechnical Commission) p 12
11. Jonkman B J 2009 TurbSim user's guide: version 1.50 Tech. Rep. TP-500-46198 (Golden, CO: National Renewable Energy Laboratory)
12. Jonkman J and Buhl M J 2005 FAST user's guide Tech. Rep. EL-500-29798 (Golden, CO: National Renewable Energy Laboratory)
13. Kelley N D 2011 Turbulence-turbine interaction: the basis for the development of the TurbSim stochastic simulator Tech. Rep. TP-5000-52353 (Golden, CO: National Renewable Energy Laboratory)
14. Kragh K A, Fleming P A and Scholbrock A 2013 Increased power capture by rotor speed dependent yaw control of wind turbines J. Sol. Energy Eng. at press
15. Malcolm D J and Hansen A 2006 WindPACT turbine rotor design study Subcontract Report SR-500-32495 (Golden, CO: National Renewable Energy Laboratory)
16. Manwell J, McGowan J and Rogers A 2009 Wind Energy Explained 2nd edn (New York: Wiley)
17. MATLAB 2010 Version 7.11.0 (R2010b) (Natick, MA: The MathWorks Inc)
18. Poore R and Lettenmaier T 2003 Alternative design study report: WindPACT advanced wind turbine drive train designs study Subcontractor Report NREL/SR-500-33196 (Golden, CO: National Renewable Energy Laboratory)
19. Rose S and Apt J 2012 Generating wind time series as a hybrid of measured and simulated data Wind Energy 15 699-715
20. Sathe A, Mann J, Barlas T, Bierbooms W and van Bussel G 2012 Influence of atmospheric stability on wind turbine loads Wind Energy at press (doi:10.1002/we.1528)
21. Seifert G 2007 Idaho Wind Data (Idaho Falls, ID: Idaho National Laboratory)
22. Vanderwende B J and Lundquist J K 2012 The modification of wind turbine performance by statistically distinct atmospheric regimes Environ. Res. Lett. 7 034035
23. Wagner R, Courtney M, Gottschall J and Lindelöw-Marsden P 2011 Accounting for the speed shear in wind turbine power performance measurement Wind Energy 14 993-1004
24. Wagner R, Courtney M, Larsen T and Paulsen U 2010 Simulation of shear and turbulence impact on wind turbine performance Tech. Rep. Risø-R-1722(EN) (Roskilde: Risø National Laboratory)
25. Wharton S and Lundquist J K 2012 Atmospheric stability affects wind turbine power collection Environ. Res. Lett. 7 014005
26. Wiser R and Bollinger M 2012 2011 Wind technologies market report Tech. Rep. (Washington, DC: US Department of Energy)