Average power losses due to wind turbine wakes are of the order of 10 to 20% of total power output in large offshore wind farms. Accurately quantifying power losses due to wakes is, therefore, an important part of overall wind farm economics. The focus of this research is to compare different types of models from computational fluid dynamics (CFD) to wind farm models in terms of how accurately they represent wake losses when compared with measurements from offshore wind farms. The ultimate objective is to improve modelling of flow for large wind farms in order to optimize wind farm layouts to reduce power losses due to wakes and loads.The research presented is part of the EC-funded UpWind project, which aims to radically improve wind turbine and wind farm models in order to continue to improve the costs of wind energy. Reducing wake losses, or even reduce uncertainties in predicting power losses from wakes, contributes to the overall goal of reduced costs. Here, we assess the state of the art in wake and flow modelling for offshore wind farms, the focus so far has been cases at the Horns Rev wind farm, which indicate that wind farm models require modification to reduce under-prediction of wake losses while CFD models typically over-predict wake losses. Further investigation is underway to determine the causes of these discrepancies.

Three-dimensional and rotational viscous effects on wind turbine blades are investigated by means of a quasi-3D Navier-Stokes model. The governing equations of the model are derived from the 3-D primitive variable Navier-Stokes equations written in cylindrical coordinates in the rotating frame of reference. The latter are integrated along the radial direction and certain assumptions are made for the mean values of the radial derivatives. The validity of these assumptions is cross-checked through fully 3-D Navier-Stokes calculations. The resulting quasi-3D model suggests that three-dimensional and rotational effects be strongly related to the local chord by radii ratio and the twist angle. The equations of the model are numerically integrated by means of a pressure correction algorithm. Both laminar and turbulent flow simulations are performed. The former is used for identifying the physical mechanism associated with the 3-D and rotational effects, while the latter for establishing semiempirical correction laws for the load coefficients, based on 2-D airfoil data. Comparing calculated and measured power curves of a stall controlled wind turbine, it is shown that the suggested correction laws may improve significantly the accuracy of the predictions. [S0098-2202(00)02702-4]

Computational fluid dynamic (CFD) methods are used in this paper to predict the power production from entire wind farms in complex terrain and to shed some light into the wake flow patterns. Two full three‐dimensional Navier–Stokes solvers for incompressible fluid flow, employing k − ϵ and k − ω turbulence closures, are used. The wind turbines are modeled as momentum absorbers by means of their thrust coefficient through the actuator disk approach. Alternative methods for estimating the reference wind speed in the calculation of the thrust are tested. The work presented in this paper is part of the work being undertaken within the UpWind Integrated Project that aims to develop the design tools for next generation of large wind turbines. In this part of UpWind, the performance of wind farm and wake models is being examined in complex terrain environment where there are few pre‐existing relevant measurements. The focus of the work being carried out is to evaluate the performance of CFD models in large wind farm applications in complex terrain and to examine the development of the wakes in a complex terrain environment. Copyright © 2011 John Wiley & Sons, Ltd.

Wind turbines with a rated power of 5 to 6 MW are now being designed and installed, mostly for offshore operation. Within the EU supported UpWind research project, the barriers for a further increase of size, up to 20 MW, are considered. These wind turbines are expected to have a rotor diameter up to 250 m and a hub height of more than 150 m. Initially, the theoretical implications of upscaling to such sizes on the weight and loads of the wind turbines are examined, where it is shown that unfavourable increases in weight and load will have to be addressed. Following that, empirical models of the increase in weight cost and loads as a function of scale are derived, based on historical trends. These include the effects of both scale and technology advancements, resulting in more favourable scaling laws, indicating that technology breakthroughs are prerequisites for further upscaling in a cost-efficient way. Finally, a theoretical framework for optimal design of large wind turbines is developed. This is based on a life cycle cost approach, with the introduction of generic models for the costs, as functions of the design parameters and using basic upscaling laws adjusted for technology improvement effects. The optimal concept or concepts is obtained as the one that minimizes the total expected costs per megawatt hour (levelized production costs).

The modelling of wind turbine wakes is investigated in this paper using a Navier-Stokes solver employing the k-ω turbulence model appropriately modifi ed for atmospheric fl ows. It is common knowledge that even single-wind turbine wake predictions with computational fl uid dynamic methods underestimate the near wake defi cit, directly contributing to the overestimation of the power of the downstream turbines. For a single-wind turbine, alternative modelling enhancements under neutral and stable atmospheric conditions are tested in this paper to account for and eventually correct the turbulence overestimation that is responsible for the faster fl ow recovery that appears in the numerical predictions. Their effect on the power predictions is evaluated with comparison with existing wake measurements. A second issue addressed in this paper concerns multi-wake predictions in wind farms, where the estimation of the reference wind speed that is required for the thrust calculation of a turbine located in the wake(s) of other turbines is not obvious. This is overcome by utilizing an induction factor-based concept: According to it, the defi nition of the induction factor and its relationship with the thrust coeffi cient are employed to provide an average wind speed value across the rotor disk for the estimation of the axial force. Application is made on the case of fi ve wind turbines in a row.Modelling of wind turbine wakes J. M. Prospathopoulos et al.