CONTINUOUS LONG-TERM TEST PROGRAM ON A UTILITY-SCALE WIND TURBINE

2006 ◽  
Author(s):  
Jose Zayas ◽  
Herbert Sutherland ◽  
Troy Patton
Keyword(s):  
Wind Turbine ◽  
Test Program ◽  
Utility Scale

Field testing of multi-variable individual pitch control on a utility-scale wind turbine

2021 ◽  
Vol 170 ◽  
pp. 1245-1256
Author(s):  
Daniel Ossmann ◽  
Peter Seiler ◽  
Christopher Milliren ◽  
Alan Danker
Keyword(s):  
Wind Turbine ◽  
Field Testing ◽  
Pitch Control ◽  
Utility Scale ◽  
Individual Pitch Control

scholarly journals Long-term changes in offshore wind power density and wind turbine capacity factor in the Iberian Peninsula (1900–2010)

Energy ◽  
2021 ◽  
Vol 226 ◽  
pp. 120364
Author(s):  
Sheila Carreno-Madinabeitia ◽  
Gabriel Ibarra-Berastegi ◽  
Jon Sáenz ◽  
Alain Ulazia
Keyword(s):  
Wind Turbine ◽  
Iberian Peninsula ◽  
Wind Power ◽  
Power Density ◽  
Capacity Factor ◽  
Offshore Wind ◽  
Offshore Wind Power ◽  
Long Term Changes ◽  
Turbine Capacity

Long Term Wind Turbine Performance Analysis Through SCADA Data: A Case Study

2021 ◽  
Author(s):  
Davide Astolfi ◽  
Gabriele Malgaroli ◽  
Filippo Spertino ◽  
Angela Amato ◽  
Andrea Lombardi ◽  
...  
Keyword(s):  
Performance Analysis ◽  
Wind Turbine ◽  
Turbine Performance

Comparison of Spar and Semisubmersible Floater Concepts of Offshore Wind Turbines Using Long-Term Analysis

2015 ◽  
Vol 137 (6) ◽  
Author(s):  
Hasan Bagbanci ◽  
D. Karmakar ◽  
C. Guedes Soares
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Transfer Functions ◽  
Probability Distributions ◽  
Offshore Wind ◽  
Short Term ◽  
Offshore Wind Turbines ◽  
Floating Wind Turbine ◽  
Offshore Floating Wind Turbine

The long-term probability distributions of a spar-type and a semisubmersible-type offshore floating wind turbine response are calculated for surge, heave, and pitch motions along with the side-to-side, fore–aft, and yaw tower base bending moments. The transfer functions for surge, heave, and pitch motions for both spar-type and semisubmersible-type floaters are obtained using the fast code and the results are also compared with the results obtained in an experimental study. The long-term predictions of the most probable maximum values of motion amplitudes are used for design purposes, so as to guarantee the safety of the floating wind turbines against overturning in high waves and wind speed. The long-term distribution is carried out using North Atlantic wave data and the short-term floating wind turbine responses are represented using Rayleigh distributions. The transfer functions are used in the procedure to calculate the variances of the short-term responses. The results obtained for both spar-type and semisubmersible-type offshore floating wind turbine are compared, and the study will be helpful in the assessments of the long-term availability and economic performance of the spar-type and semisubmersible-type offshore floating wind turbine.

Long-Term Dynamic Monitoring of an Offshore Wind Turbine

2013 ◽  
pp. 253-267 ◽  
Author(s):  
Christof Devriendt ◽  
Filipe Magalhães ◽  
Mahmoud El Kafafy ◽  
Gert De Sitter ◽  
Álvaro Cunha ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Offshore Wind ◽  
Dynamic Monitoring ◽  
Offshore Wind Turbine

scholarly journals Inter-annual variability of wind climates and wind turbine annual energy production

2018 ◽  
Author(s):  
Sara C. Pryor ◽  
Tristan J. Shepherd ◽  
Rebecca J. Barthelmie
Keyword(s):  
Standard Deviation ◽  
Wind Energy ◽  
Wind Turbine ◽  
Energy Production ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Speeds ◽  
Annual Variability ◽  
Eastern Usa

Abstract. Inter-annual variability (IAV) of expected annual energy production (AEP) from proposed wind farms plays a key role in dictating project financing. IAV in pre-construction projected AEP and the difference in 50th and 90th percentile (P50 and P90) AEP derives in part from variability in wind climates. However, the magnitude of IAV in wind speeds at/close to wind turbine hub-heights is poorly constrained and maybe overestimated by the 6 % standard deviation of annual mean wind speeds that is widely applied within the wind energy industry. Thus there is a need for improved understanding of the long-term wind resource and the inter-annual variability therein in order to generate more robust predictions of the financial value of a wind energy project. Long-term simulations of wind speeds near typical wind turbine hub-heights over the eastern USA indicate median gross capacity factors (computed using 10-minute wind speeds close to wind turbine hub-heights and the power curve of the most common wind turbine deployed in the region) that are in good agreement with values derived from operational wind farms. The IAV of annual mean wind speeds at/near to typical wind turbine hub-heights in these simulations is lower than is implied by assuming a standard deviation of 6 %. Indeed, rather than in 9 in 10 years exhibiting AEP within 0.9 and 1.1 times the long-term mean AEP, results presented herein indicate that over 90 % of the area in the eastern USA that currently has operating wind turbines simulated AEP lies within 0.94 and 1.06 of the long-term average. Further, IAV of estimated AEP is not substantially larger than IAV in mean wind speeds. These results indicate it may be appropriate to reduce the IAV applied to pre-construction AEP estimates to account for variability in wind climates, which would decrease the cost of capital for wind farm developments.

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