Atmospheric pressure gradients and Coriolis forces provide geophysical limits to power density of large wind farms

2021 ◽  
Vol 281 ◽  
pp. 116048
Author(s):  
Enrico G.A. Antonini ◽  
Ken Caldeira
Keyword(s):  
Power Density ◽  
Atmospheric Pressure ◽  
Wind Farms ◽  
Pressure Gradients ◽  
Coriolis Forces ◽  
Large Wind

scholarly journals Wake properties and power output of very large wind farms for different meteorological conditions and turbine spacings: A large-eddy simulation case study for the German Bight

2021 ◽  
Author(s):  
Oliver Maas ◽  
Siegfried Raasch
Keyword(s):  
Boundary Layer ◽  
Power Density ◽  
Boundary Layers ◽  
Power Output ◽  
German Bight ◽  
Wind Farm ◽  
Wind Farms ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Large Wind

Abstract. Germany’s expansion target for offshore wind power capacity of 40 GW by the year 2040 can only be reached if large portions of the Exclusive Economic Zone in the German Bight are equipped with wind farms. Because these wind farm clusters will be much larger than existing wind farms, it is unknown how they affect the boundary layer flow and how much power they will produce. The objective of this large-eddy-simulation study is to investigate the wake properties and the power output of very large potential wind farms in the German Bight for different turbine spacings, stabilities and boundary layer heights. The results show that very large wind farms cause flow effects that small wind farms do not. These effects include, but are not limited to, inversion layer displacement, counterclockwise flow deflection inside the boundary layer and clockwise flow deflection above the boundary layer. Wakes of very large wind farms are longer for shallower boundary layers and smaller turbine spacings, reaching values of more than 100 km. The wake in terms of turbulence intensity is approximately 20 km long, where longer wakes occur for convective boundary layers and shorter wakes for stable boundary layers. Very large wind farms in a shallow, stable boundary layer can excite gravity waves in the overlying free atmosphere, resulting in significant flow blockage. The power output of very large wind farms is higher for thicker boundary layers, because thick boundary layers contain more kinetic energy than thin boundary layers. The power density of the energy input by the geostrophic pressure gradient limits the power output of very large wind farms. Because this power density is very low (approximately 2 W m−2), the installed power density of very large wind farms should be small to achieve a good wind farm efficiency.

Large Wind Farms and the Scalar Flux over an Heterogeneously Rough Land Surface

2014 ◽  
Vol 153 (3) ◽  
pp. 471-495 ◽  
Author(s):  
Marc Calaf ◽  
Chad Higgins ◽  
Marc B. Parlange
Keyword(s):  
Land Surface ◽  
Wind Farms ◽  
Scalar Flux ◽  
Large Wind

A Comparative Study of the Influence of Different Wake Models on Wind Farm Layout Optimization

2021 ◽  
Author(s):  
Puyi Yang ◽  
Hamidreza Najafi
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
Vital Role ◽  
Layout Optimization ◽  
Zone Model ◽  
Wind Farm Layout ◽  
Yaw Control ◽  
Wind Farm Layout Optimization ◽  
Wake Model ◽  
Large Wind

Abstract The accuracy of analytical wake models applied in wind farm layout optimization (WFLO) problems plays a vital role in the present era that the high-fidelity methods such as LES and RANS are still not able to handle an optimization problem for large wind farms. Based on a verity of analytical wake models developed in the past decades, FLOw Redirection and Induction in Steady State (FLORIS) has been published as a tool integrated several widely used wake models and the expansions for them. This paper compares four wake models selected from FLORIS by applying three classical WFLO scenarios. The results illustrate that the Jensen wake model is the fastest one but the defect of underestimation of velocity deficit is obvious. The Multi Zone model needs to be applied additional tunning on the parameters inside the model to fit specific wind turbines. The Gaussian-Curl wake model as an advanced expansion of the Gaussian wake model does not perform an observable improvement in the current study that the yaw control is not included. The default Gaussian wake model is recommended to be used in the WFLO projects which implemented under the FLROIS framework and has similar wind conditions with the present work.

scholarly journals Performance and Equivalent Loads of Wind Turbines in Large Wind Farms

2017 ◽  
Vol 854 ◽  
pp. 012001 ◽  
Author(s):  
Søren J. Andersen ◽  
Jens N. Sørensen ◽  
Robert F. Mikkelsen
Keyword(s):  
Wind Turbines ◽  
Wind Farms ◽  
Large Wind

Wind farm cooperative control for optimal power generation

2018 ◽  
Vol 42 (6) ◽  
pp. 547-560 ◽  
Author(s):  
Fa Wang ◽  
Mario Garcia-Sanz
Keyword(s):  
Power Generation ◽  
Wind Turbines ◽  
Cooperative Control ◽  
Wind Farm ◽  
Wind Farms ◽  
Practical Method ◽  
Individual Case ◽  
Power Coefficient ◽  
The Individual ◽  
Large Wind

The power generation of a wind farm depends on the efficiency of the individual wind turbines of the farm. In large wind farms, wind turbines usually affect each other aerodynamically at some specific wind directions. Previous studies suggest that a way to maximize the power generation of these wind farms is to reduce the generation of the first rows wind turbines to allow the next rows to generate more power (coordinated case). Yet, other studies indicate that the maximum generation of the wind farm is reached when every wind turbine works at its individual maximum power coefficient CPmax (individual case). This article studies this paradigm and proposes a practical method to evaluate when the wind farm needs to be controlled according to the individual or the coordinated case. The discussion is based on basic principles, numerical computations, and wind tunnel experiments.

Assessment of wind energy potential and characteristics in Qatar for clean electricity generation

2021 ◽  
pp. 0309524X2110438
Author(s):  
Carlos Méndez ◽  
Yusuf Bicer
Keyword(s):  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Rose ◽  
Energy Potential ◽  
Wind Power Density ◽  
Wind Speeds ◽  
Wind Energy Potential

The present study analyzes the wind energy potential of Qatar, by generating a wind atlas and a Wind Power Density map for the entire country based on ERA-5 data with over 41 years of measurements. Moreover, the wind speeds’ frequency and direction are analyzed using wind recurrence, Weibull, and wind rose plots. Furthermore, the best location to install a wind farm is selected. The results indicate that, at 100 m height, the mean wind speed fluctuates between 5.6054 and 6.5257 m/s. Similarly, the Wind Power Density results reflect values between 149.46 and 335.06 W/m2. Furthermore, a wind farm located in the selected location can generate about 59.7437, 90.4414, and 113.5075 GWh/y electricity by employing Gamesa G97/2000, GE Energy 2.75-120, and Senvion 3.4M140 wind turbines, respectively. Also, these wind farms can save approximately 22,110.80, 17,617.63, and 11,637.84 tons of CO2 emissions annually.

scholarly journals Partitioning approach for large wind farms: Active power control for optimizing power reserve

2018 ◽  
Author(s):  
Sara Siniscalchi-Minna ◽  
Carlos Ocampo-Martinez ◽  
Fernando D. Bianchi ◽  
Mikel De-Prada-Gil ◽  
Bart De-Schutter
Keyword(s):  
Power Control ◽  
Wind Farms ◽  
Active Power ◽  
Active Power Control ◽  
Large Wind

scholarly journals Tuning turbine rotor design for very large wind farms

2018 ◽  
Vol 474 (2220) ◽  
pp. 20180237 ◽  
Author(s):  
Takafumi Nishino ◽  
William Hunter
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
Theoretical Method ◽  
Turbine Rotor ◽  
Aerodynamic Optimization ◽  
Rotor Design ◽  
Coupling Procedure ◽  
Future Extension ◽  
Large Wind ◽  
Bem Theory

A new theoretical method is presented for future multi-scale aerodynamic optimization of very large wind farms. The new method combines a recent two-scale coupled momentum analysis of ideal wind turbine arrays with the classical blade-element-momentum (BEM) theory for turbine rotor design, making it possible to explore some potentially important relationships between the design of rotors and their performance in a very large wind farm. The details of the original two-scale momentum model are described first, followed by the new coupling procedure with the classical BEM theory and some example solutions. The example solutions, obtained using a simplified but still realistic NREL S809 aerofoil performance curve, illustrate how the aerodynamically optimal rotor design may change depending on the farm density. It is also shown that the peak power of the rotors designed optimally for a given farm (i.e. ‘tuned' rotors) could be noticeably higher than that of the rotors designed for a different farm (i.e. ‘untuned' rotors) even if the blade pitch angle is allowed to be adjusted optimally during the operation. The results presented are for ideal very large wind farms and a possible future extension of the present work for real large wind farms is also discussed briefly.

scholarly journals Flow visualization using momentum and energy transport tubes and applications to turbulent flow in wind farms

2013 ◽  
Vol 715 ◽  
pp. 335-358 ◽  
Author(s):  
Johan Meyers ◽  
Charles Meneveau
Keyword(s):  
Turbulent Flow ◽  
Flow Visualization ◽  
Energy Transport ◽  
Three Dimensional ◽  
Wind Farms ◽  
Mean Flow ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Using Data ◽  
Large Wind

AbstractAs a generalization of the mass–flux based classical stream tube, the concept of momentum and energy transport tubes is discussed as a flow visualization tool. These transport tubes have the property that no fluxes of momentum or energy exist over their respective tube mantles. As an example application using data from large eddy simulation, such tubes are visualized for the mean-flow structure of turbulent flow in large wind farms, in fully developed wind-turbine-array boundary layers. The three-dimensional organization of energy transport tubes changes considerably when turbine spacings are varied, enabling the visualization of the path taken by the kinetic energy flux that is ultimately available at any given turbine within the array.

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