Offshore wind turbines intend to take a rapidly growing share in the electric mix. The design, installation, and exploitation of these industrial assets are regulated by international standards, providing generic guidelines. Constantly, new projects reach unexploited wind resources, pushing back installation limits. Therefore, turbines are increasingly subject to uncertain environmental conditions, making long-term investment decisions riskier (at the design or end-of-life stage). Fortunately, numerical models of wind turbines enable to perform accurate multi-physics simulations of such systems when interacting with their environment. The challenge is then to propagate the input environmental uncertainties through these models and to analyze the distribution of output variables of interest. Since each call of such a numerical model can be costly, the estimation of statistical output quantities of interest (e.g., the mean value, the variance) has to be done with a restricted number of simulations. To do so, the present paper uses the kernel herding method as a sampling technique to perform Bayesian quadrature and estimate the fatigue damage. It is known from the literature that this method guarantees fast and accurate convergence together with providing relevant properties regarding subsampling and parallelization. Here, one numerically strengthens this fact by applying it to a real use case of an offshore wind turbine operating in Teesside, UK. Numerical comparison with crude and quasi-Monte Carlo sampling demonstrates the benefits one can expect from such a method. Finally, a new Python package has been developed and documented to provide quick open access to this uncertainty propagation method.

Accurate and reliable computation of the aerodynamic characteristics of wind turbines is very important for the development of new efficient designs. The flow around a wind turbine is modeled by a permeable disc (PD), solved through the Unsteady Reynolds-Averaged Navier–Stokes equations (URANS), here named PD/URANS method. The finite volume method and a total variation diminishing (TVD) scheme solve numerically the flow governing equations. The turbulent flow in the wake of the wind turbine is simulated utilising a one-equation turbulence model. The Glauert correction calculation considers a uniform normal force distribution (CT) on the virtual permeable disc applied to the flow, while the axial induction factor is obtained directly from the numerical solution of the URANS equations. The numerical axial induction factor obtained agrees fairly well with Glauert correction, except if the flow behind the turbine is highly unsteady and Reynolds number dependent.

In this study, the aerodynamic characteristics of a vertical-axis wind turbine blade coupled with a high-lift device, such as the Gurney flap at the trailing edge, are investigated. For numerical analysis, the force element theory is used to understand how the Gurney flap influences the force evolution of the lift-type vertical-axis wind turbine. This study shows that the lift and drag can be respectively approximated into four elements, which are induced by volume vorticity, rotational velocity, angular acceleration and surface friction of the flow around the blades. Based on the perspective of the force element theory, the present simulation provides a clear picture of how the Gurney flap influences the formation of the aerodynamic force elements during a rotational cycle for a vertical-axis wind turbine. Simulation results show that the contributions mainly result from the surface vorticities, the rotational acceleration of the airfoil, and the acceleration of the surface.

Computational fluid dynamics (CFD) has been used by numerous researchers for the simulation of flows around wind turbines. Since the 2000s, the experiments of NREL phase VI blades for blind comparison have been a de-facto standard for numerical software on the prediction of full scale horizontal axis wind turbines (HAWT) performance. However, the characteristics of vortex structures in the wake, whether for modeling the wake or for understanding the aerodynamic mechanisms inside, are still not thoroughly investigated. In the present study, the flow around N-REL phase VI blades was numerically simulated, and the results of the wake field were compared with the experimental ones of a one-to-eight scaled model in a low-speed wind tunnel. A good agreement between simulation and experimental results was achieved for the evaluation of overall performances. The simulation captured the complete formation procedure of tip vortex structure from the blade. Quantitative analysis showed the streamwise translation movement of vortex cores. Both the initial formation and the damping of vorticity in near wake field were predicted. These numerical results showed good agreements with the measurements. Moreover, wind tunnel wall effects were also investigated on these vortex structures, and it revealed further radial expansion of the helical vortical structures in comparison with the free-stream case.

The main target of this paper is to determine the seasonal features of the wind speed inthe northwestern of Senegal and to assess the cost of annual energy output using windturbines provided from several manufactures. The wind data used for this study werecollected in four sites located in the northwestern coast of Senegal and cover the periodof one year. The seasonal mean wind speed and the annual distribution curves were obtainedby using the Weibull distribution function. A technical assessment of electricitygeneration from five big wind turbines which power is between 640 kW and 2000 kW and fromsix small wind turbines which power is between 250 W and 10 kW were carried out. Theresults obtained show that the lower cost (0.0265 €/kWh in Sokhar) was observed for thewind turbine Ecotècnia 62. The highest cost was 0.5103 €/kWh (in Gandon) observed for thetechnology of Alize. All wind turbines was better suited to the site of Sokhar with thehighest capacity factor and the lowest cost of output energy.