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Power Curve Uncertainties of Rotor Equivalent Wind Speed
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Klaus Franke Deutsche WindGuard Consulting GmbH, Germany POWER CURVE UNCERTAINTIES OF ROTOR EQUIVALENT WIND SPEED ![]() Abstract ID: 409 Poster code: PO.277 | Download poster: ![]() |
Presenter's biography
Biographies are supplied directly by presenters at WindEurope 2016 and are published here uneditedKlaus Franke studied physics at the University of Bremen finishing his university tenure with a doctorate degree in atmospheric physics. He then started work with WindGuard Group to apply his knowledge of atmospheric processes and data analysis skills on power curve and wind resource measurements. Here he coordinated international measurement projects with both met masts and remote sensing devices. One major field of expertise is the usage and testing of remote sensing devices. He was involved in the development of one of the world’s first accredited calibration station for remote sensing devices and has performed several classifications of such instruments.
Abstract
Power Curve Uncertainties of Rotor Equivalent Wind Speed
Introduction
Rotor Equivalent Wind Speed (REWS) is the wind speed corresponding to the kinetic energy flux through the total swept area of a wind turbine. It considers change of wind speed and wind direction over the substantial height of modern day multi-megawatt turbines. Introduced by the upcoming revision of the IEC 61400-12-1, this wind speed definition aims at deriving power curves representative for a wider range of environmental conditions than current state of the art power curves based on hub height wind speed (HHWS). In this work, the challenge of handling measurement uncertainties of this innovative measurement method is addressed.
Approach
Measurement data of power curve measurements at different sites in Germany, Denmark and the United States were analysed. During the evaluated measurement periods a measurement mast equipped with cup anemometers and a ground based LiDAR (Light Detecting And Ranging) where simultaneously installed in an adequate distance of a wind turbine. For each data set the power curve is evaluated with four wind speed definitions. These wind speed definitions are HHWS derived from cup anemometer measurements, HHWS from LiDAR measurements, REWS from LiDAR measurements and REWS measured by a combination of mast and LiDAR measurements. For each derived power curve a comprehensive uncertainty analysis according to the current draft version CDV IEC 61400-12-1, ed. 2 is performed.
Main body of abstract
REWS is calculated from LiDAR measurements of wind speed and wind direction in more than three heights evenly distributed between lower and upper rotor edge. In combining these measurements to one wind speed value, sophisticated error propagation of individual uncertainty components is necessary to get realistic error estimates. Especially the correct assumption about correlation of uncertainty components between different wind speed measurements can significantly influence the resulting measurement uncertainty.
In addition, the revision of the standard also introduces additional uncertainty components not considered in the current version. E.g. an uncertainty arising from the lack of knowledge of the vertical wind speed profile has to be considered when using HHWS. As a consequence uncertainties of power curves measured according to different versions of the standard are not comparable. As example, one of the analysed datasets show that the uncertainty in AEP of the HHWS power curve measured with a cup anemometer calculated according to the current standard for an annual mean wind speed of 7 m/s is 5.1% compared to the uncertainty of 6.5% calculated according to the upcoming revision.
In this one case, the uncertainty in measured AEP for the different wind speed measurement methods as calculated with the upcoming revision are as follows: cup measurement HHWS 6.5%, LiDAR Measurement HHWS 7.4%, LiDAR Measurement REWS 6.3%. This uncertainty can be significantly reduced if hub height cup anemometry is combined with LiDAR measurements of the vertical profile of the wind field. In the given example the final uncertainty of that method is at 5.0%.
Conclusion
With the requirements of the upcoming revision of the IEC 61400-12-1 the need of a carefully executed uncertainty analysis arises. Especially a list of uncertainty components not address in the current standard can lead to higher power curve uncertainties. However, when using a combination of hub height wind speed measured by a cup anemometer and LiDAR measurements of the vertical wind field profile AEP uncertainties of the size of current power curves can be achieved.
Learning objectives
- assess uncertainties of power curves as introduced by new version standard IEC 61400-12-1
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