Wind Energy Prediction in Highly Complex Terrain by Computational Fluid Dynamics

With rising levels of wind power penetration in global electricity production, the relevance of wind power prediction is growing. More accurate forecasts reduce the required total amount of energy reserve capacity needed to ensure grid reliability and the risk of penalty for wind farm operators. This study analyzes the Computational Fluid Dynamics (CFD) software WindSim regarding its ability to perform accurate wind power predictions in complex terrain. Simulations of the wind field and wind farm power output in the Swiss Jura Mountains at the location of the Juvent Wind Farm during winter were performed. The study site features the combined presence of three complexities: topography, heterogeneous vegetation including forest, and interactions between wind turbine wakes. Hence, it allows a comprehensive evaluation of the software. Various turbulence models, forest models, and wake models, as well as the effects of domain size and grid resolution were evaluated against wind and power observations from nine Vestas V90’s 2.0-MW turbines. The results show that, with a proper combination of modeling options, WindSim is able to predict the performance of the wind farm with sufficient accuracy.

[1]  T. Wallbank.  WindSim Validation Study CFD validation in Complex terrain , 2008 .

[2]  S. Ramechecandane,et al.  Numerical Investigations on Wind Flow over Complex Terrain , 2012 .

[3]  S. Orszag,et al.  Development of turbulence models for shear flows by a double expansion technique , 1992 .

[4]  Y. Gagnon,et al.  Assessment of wind power plants with limited wind resources in developing countries: Application to Ko Yai in southern Thailand , 2017 .

[5]  Davide Astolfi,et al.  Numerical and Experimental Methods for Wake Flow Analysis in Complex Terrain , 2015 .

[6]  M. Adaramola,et al.  Validation of kinematic wind turbine wake models in complex terrain using actual windfarm production data , 2017 .

[7]  L. Mathys.  A discrete Forest in a continuous Landscape Investigating Interactions between Natural Resource Management and Sustainable Development , 2007 .

[8]  Francesco Castellani,et al.  Wake Modeling with the Actuator Disc Concept , 2012 .

[9]  Görkem Teneler.  Wind Flow Analysis on a Complex Terrain : a reliability study of a CFD tool on forested area including effects of forest module , 2011 .

[10]  René Cattin,et al.  Validation of CFD Wind Resource Modeling in Highly Complex Terrain , 2006 .

[11]  D. Wilcox.  Reassessment of the scale-determining equation for advanced turbulence models , 1988 .

[12]  Fernando Porté-Agel,et al.  Large-eddy simulation of atmospheric boundary layer flow through wind turbines and wind farms , 2011 .

[13]  A. Llombart,et al.  Performance analysis of wind resource assessment programs in complex terrain , 2006 .

[14]  F. Porté-Agel,et al.  Analytical Modeling of Wind Farms: A New Approach for Power Prediction , 2016 .

[15]  Christophe Sanz,et al.  ONE- and TWO-Equation Models for Canopy Turbulence , 2004 .

[16]  Bernhard Stoevesandt,et al.  Validation of the simpleFoam (RANS) solver for the atmospheric boundary layer in complex terrain , 2014 .

[17]  F. Porté-Agel,et al.  Wind turbine wakes over hills , 2018, Journal of Fluid Mechanics.

[18]  Luís Frölén Ribeiro,et al.  Linear and nonlinear models in wind resource assessment and wind turbine micro-siting in complex terrain , 2008 .

[19]  Davide Astolfi,et al.  Investigation of terrain and wake effects on the performance of wind farms in complex terrain using numerical and experimental data , 2017, Wind Energy.

[20]  D. Wilcox.  Formulation of the k-w Turbulence Model Revisited , 2008 .

[21]  A. Z. Dhunny,et al.  Wind energy evaluation for a highly complex terrain using Computational Fluid Dynamics (CFD) , 2017 .

[22]  O. P. Rahi,et al.  A comprehensive review of wind resource assessment , 2017 .