Evaluation of an offshore wind farm computational fluid dynamics model against operational site data

OCEAN ENGINEERING

卷:193

Article

Richmond, M.^1,2  Antoniadis, A.³  Wang, L.⁴  Kolios, A.²  Al-Sanad, S.⁵  Parol, J.⁵ 

[1] Cranfield Univ, Offshore Energy Engn Ctr, Cranfield MK43 0AL, Beds, England

[2] Univ Strathclyde, Dept Naval Architecture Ocean & Marine Engn, Glasgow G4 0LZ, Lanark, Scotland

[3] Cranfield Univ, Computat Engn Sci Ctr, Cranfield MK43 0AL, Beds, England

[4] Coventry Univ, Sch Mech Aerosp & Automot Engn, Coventry CV1 5FB, W Midlands, England

[5] Kuwait Inst Sci Res, Sustainabil & Reliabil Infrastruct Program, Kuwait, Kuwait

关键词: Actuator disk;    Offshore wind farm;    CFD;    SCADA;    Site data;    Turbulence models;   

DOI  :  10.1016/j.oceaneng.2019.106579

来源: Elsevier

【 摘 要 】

Modelling wind turbine wake effects at a range of wind speeds and directions with actuator disk (AD) models can provide insight but also be challenging. With any model it is important to quantify the level of error, but this can also present a challenge when comparing a steady-state model to measurement data with scatter. This paper models wind flow in a wind farm at a range of wind speeds and directions using an AD implementation. The results from these models are compared to data collected from the actual farm being modelled. An extensive comparison is conducted, constituted from 35 cases where two turbulence models, the standard k-epsilon and k-omega SST are evaluated. The steps taken in building the models as well as processes for comparing the AD computational fluid dynamics (CFD) results to real-world data using the regression models of ensemble bagging and Gaussian process are outlined. Turbine performance data and boundary conditions are determined using the site data. Modifications to an existing opensource AD code are shown so that the predetermined turbine performance can be implemented into the CFD model. Steady state solutions are obtained with the OpenFOAM CFD solver. Results are compared in terms of velocity deficit at the measurement locations. Using the standard k-epsilon model, a mean absolute error for all cases together of roughly 8% can be achieved, but this error changes for different directions and methods of evaluating it.

【 授权许可】

Free