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Delegates are invited to meet and discuss with the poster presenters in this topic directly after the session 'Optimising measurement strategies to maximise project value: Is the industry making false economies at the expense of project value?' taking place on Tuesday, 11 March 2014 at 11:15-12:45. The meet-the-authors will take place in the poster area.

Maria Bullido Garcia Meteodyn, France
Co-authors:
Celine BEZAULT (1) F P Zixiao JIANG (1) Maria BULLIDO GARCIA (1)
(1) Meteodyn, NANTES, France (2) Meteodyn China, Beijing, China

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Abstract

Validation of wind resource assessment process based on CFD modeling

Introduction

Wind resource assessment requires nowadays more efficient tools to provide an accurate evaluation of production in order to obtain a better loan. As onshore wind farms are built in complex terrain, it is necessary to find a new method to provide a fine evaluation. This is the reason why CFD modeling has become a standard for WRA in complex terrain. This paper presents the process to perform a WRA by using CFD technology.

Approach

This wind resource assessment is focused on the wind speed and energy yield prediction carried out for a 29MW wind farm project located in Europe in a complex and forested area. Net energy prediction P50 is compared against real wind farm performance data during a blind test organized by EWEA.

Main body of abstract

The site is considered as complex because of elevation and roughness changes; it is now common to use CFD modeling to reduce the error and uncertainties introduced by wind extrapolation. After performing a Measure-Correlate-Predict (MCP) method to obtain meteorological data representative of local meteorology thanks to long term data at a station and local data at met masts, the present study is carried out with CFD Meteodyn WT. The numerical schema that solves the Navier Stokes equations, as well as the computation efficiency are discussed. Wind speed as well as wake effect are evaluated.
The accuracy of the wind modeling is investigated by checking the cross validation between the different met masts at 7 locations around the site. Both the extrapolated wind speed and turbulence intensity are compared to the measurement data provided by the EWEA. The cross prediction shows that the extrapolation introduces only a slight uncertainty on the assessment. Probability of exeedance of production are analyze for the whole park.


Conclusion

The long-term data at one reference mast is used for the energy yield calculations. The predicted energy yield of each wind turbine is compared to the real performance data. It shows that the assessment predicts well the performance data of the wind farm as well as the contribution of each turbine.


Learning objectives
This presentation will allow the audience to:
- Recognize the gain on the accuracy of wind data extrapolation provided by CFD modeling.
- Improve the understanding of the numerical solver integrated in the CFD method.
- Carry out a common procedure to validate a wind flow modeling and estimate its uncertainty on the energy yield prediction.