Pena Diaz, Alfredo

Rathmann, Ole

Réthoré, Pierre-Elouan

Online Research Database In Technology

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Revising the WASP-Park&amp;#039;S model wake decay coefficient for different atmospheric stabilities to better predict wind farm outputs

                       General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.  • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal   If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.     Downloaded from orbit.dtu.dk on: Dec 20, 2017Revising the WASP-Park&#039;S model wake decay coefficient for differentatmospheric stabilities to better predict wind farm outputsPena Diaz, Alfredo; Rathmann, Ole Steen; Réthoré, Pierre-ElouanPublished in:Proceedings of EWEA 2012 - European Wind Energy Conference &amp; ExhibitionPublication date:2012Document VersionPublisher's PDF, also known as Version of recordLink back to DTU OrbitCitation (APA):Pena Diaz, A., Rathmann, O., & Réthoré, P-E. (2012). Revising the WASP-Park&#039;S model wake decaycoefficient for different atmospheric stabilities to better predict wind farm outputs. In Proceedings of EWEA 2012- European Wind Energy Conference & Exhibition European Wind Energy Association (EWEA).ABSTRACT ID:   15Theme: RESOURCE ASSESSMENT  Topic:  Resources offshoreREVISING THE WASP-PARK&AMP;#039;S MODEL WAKE DECAY COEFFICIENT FOR DIFFERENT ATMOSPHERIC STABILITIES TO BETTERPREDICT WIND FARM OUTPUTSAlfredo Peña(1)  (F)  (P) Ole Rathmann(1) Pierre-Elouan Rethore(1) (1) DTU Wind Energy, Roskilde, DenmarkIntroductionPrediction of wind farm power outputs is a difficult task, particularly for large-size wind farms—above 5 km in extension—and at sites where thevariation in atmospheric stability conditions is strong. Computational Fluid Dynamics (CFD) methods have been applied extensively for multipleturbines and small wind farms using Large Eddy Simulation (LES) and on larger wind farms using Reynolds Averaged Navier Stokes (RANS)turbulence models. LES methods remain far too computationally expensive to be used as a design tool, and still have some issues to preservephysical turbulence over very large distances. 2eq-RANS methods have some numerical and physical limitations and they approach the mutliscalephysics of wind turbine wake using a simplistic single scale model [1]. The vast majority of the CFD methods assume neutral atmospheric conditions.  ApproachOn a long-term basis, near-neutral atmospheres are the most frequent stability conditions at many wind farm sites, and under such conditions the CFDflow models’ envelope is rather valid. However, when using any type of model (CFD- or engineering-based) to predict the wind farm power output atsites biased to unstable or stable conditions or on a short-term basis (required by the wind farm operators to bid energy days or hours ahead), theerrors might be simply too large.Main body of abstractAlthough engineering wake models are also based in many assumptions and restricted to small/medium-size wind farms, they are million times fasterthan those RANS/LES-based and thus can be used for short-term wind farm power predictions under a wide range of scenarios.  The Park model [2]used in the wind atlas analysis and application program (WAsP) [3] makes use of the wake decay coefficient to estimate the wind speed deficitdownstream of a(a cluster of) wind turbine(s). [4] found that in order to match the wind speed deficits estimated by the infinite wind farm boundarylayer model of Frandsen [5] to those of the Park model (computed for a infinite wind farm), the wake decay coefficient had to be modified dependingon the atmospheric stability condition, surface roughness and turbine to turbine distance.ConclusionHere we present the analysis of power output and wind speed deficits for a range of atmospheric stability conditions of a large offshore wind farm. Thepower output is found to be highly dependent on atmospheric stability; the more stable the atmosphere the lower the power output and the higher thewind speed deficit. Using the findings in [4], i.e. using the WAsP-Park wake model but varying the wake decay coefficient, we are able to better predictthe power output of the wind farm under all stability conditions compared to that given by the model using the default wake decay coefficient values.We therefore suggest that for large wind farms, particularly offshore, the wake decay coefficient should be decreased slowly along the wind farm andthat this reduction should be higher the more stable the conditions are.[1] Rethoré P.-E. (2009) Wind turbine wake in atmospheric turbulence. Risø-PhD-53(EN), Risø DTU, Roskilde [2] Katic I., Høstrup J. and Jensen N. O. (1985) A simple model for cluster efficiency. Proc. Of the European Wind Energy Association Conference &Exhibition, Rome[3] Mortensen N. G., Heathfield D. N., Myllerup L., Landberg L. and Rathmann O. (2007) Getting started with WAsP 9. Technical reportRisø-I-2571(EN), Risø National Laboratory, Roskilde [4] Peña A. and Rathmann O. (2011) The atmospheric stability dependent infinite wind farm and wake decay coefficient, Wind Energy, in review[5] Frandsen S. (1992) On the wind speed reduction in the center of large clusters of wind turbines. J. Wind Eng. Ind. Aero. 39:251—265

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Revising the WASP-Park&#039;S model wake decay coefficient for different atmospheric stabilities to better predict wind farm outputs

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Revising the WASP-Park&amp;#039;S model wake decay coefficient for different atmospheric stabilities to better predict wind farm outputs

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Online Research Database In Technology

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Revising the WASP-Park'S model wake decay coefficient for different atmospheric stabilities to better predict wind farm outputs