Session E15: Energy: Wind Power I

Atmospheric flow over real terrain topography: Numerical simulations against Experimental data and Theoretical models

The application of reduced order models for the estimation of local atmospheric flows in presence of complex terrain topography is challenged by the variety of the terrain geometrical features and of the atmospheric flow parameters. As an example, during the assessment of new wind farm site there is the need to accurately estimate how the terrain topography affects the local flow features and, as a consequence, the Annual Energy Production.

In this study we try to reconcile the theoretical models of flows over rough surfaces with numerical and experimental data of the flow over real terrain topography. We consider the complex terrain of the Perdigão site, in Portugal. This site consists of two parallel ridges with a wind turbine located on the top of one of the ridges. In 2017 a field campaign collected data at several locations. We carried out Large Eddy Simulations of the flow over the site topography and compared them with experimental data. Given the resemblance between the Perdigão site with regular rough surfaces, we can compare data from numerical simulation with theoretical models both at the macroscale level, i.e. the effect of terrain topography on the atmospheric boundary layer, and at the microscale level, i.e. the vegetation that acts as roughness for the local flow.   

Pressure gradient effects on the wake of a model wind turbine in a turbulent boundary layer

Wind tunnel experiments were performed to study the effect of constant pressure gradients (PG) from the wall topography on the wake of a model wind turbine. Particle image velocimetry (PIV) was used to characterize the near and intermediate wake regions, whereas turbine power output was obtained at high temporal resolution. We explored five cases, including two favorable, two adverse pressure gradients, and a reference scenario with negligible pressure gradient. The result shows that pressure gradient induces a wake deflection and modulates the turbine wake; however, they imposed relatively small variations on turbulence kinetic energy and kinematic shear stress. This indicates a comparatively dominant effect of the bulk flow acceleration and deceleration on the flow recovery. Based on this, we propose a simple formulation. We first modeled the base flow profile over escarpments through a linearized perturbation method; the wake profiles are then acquired by solving the integral cross-stream streamwise momentum equation. It reasonably estimates the flow profile and PG-conditioned power output variations. This formulation can aid insight into wind-farm layout design in mild escarpment topographies.   

Field experiments of power generation using HAWT fitted with hydrostatic transmission

In this study, we replace the mechanical drive train with a hydrostatic transmission which includes a hydraulic pump connected directly to the rotor of the wind turbine. The integration of the hydrostatic transmission into the wind turbine system presents multiple advantages, including: lower LCOE, lower center of gravity and enables, a variable input and constant output in terms of rotational speed. The lower stiffness compared with the mechanical drivetrain, alongside the hydraulic capacitance, introduces a damping effect on the fluctuations, reducing fatigue of the drive train. Field experiments and a cyber-physical test-bench of the wind turbine’s behavior are studied using over a broad range of external conditions. Furthermore, the hydraulic wind turbine shows an efficiency in the range of ~75%.  In addition. the power spectrum model by Tobin et al. (2015) is used to analyze the response of the wind turbine with the hydrostatic transmission.   

Parameter uncertainty quantification of wake models to analyze effects of wake superposition

Low-fidelity wake models are used for control of wind turbines and layout optimization for wind farms. Wake models contain parameters that are tuned with experimental data, but their uncertainty is often neglected. We estimate the parameter uncertainty of a Gaussian wake model using Markov-chain Monte Carlo, and we consider the effects of different superposition methods and atmospheric stability. Posterior distributions of the uncertain parameters are generated using data from large eddy simulations and physically-constrained Gaussian priors. Then, Monte Carlo wake model predictions are generated using samples from the posterior distributions. The results show that the mean and variance of the wake expansion coefficient tend to increase in the downstream region of a wind farm. The posteriors for the wake expansion coefficient are sensitive to the choice of superposition method: four of the five superposition methods under consideration demonstrated this trend, but a sum-of-squares method was an outlier. Furthermore, we examine the influence of atmospheric stability on the posterior distribution of wake model parameters. Quantifying the uncertainty of wake model parameters enables the uncertainty quantification of wake model predictions, such as annual energy production.   

Can turbines benefit from wind veer?

Wind direction variation with height (wind veer) frequently occurs in the atmospheric surface layer and can impose a substantial impact on utility-scale wind turbine operations. Using the 10-year dataset from Eolos wind energy station hosting a 2.5 MW turbine, we identify four scenarios of wind veer based on the trends of wind direction change in turbine upper and lower rotors: VV, (upper rotor: veering, lower rotor: veering), VB (upper rotor: veering, lower rotor: backing), BV (upper rotor: backing, lower rotor: veering), BB (upper rotor: backing, lower rotor: backing). These veer scenarios can yield different influences on the lift and drag acting on different rotor sections, leading to turbine power deficit and surplus depending on specific turbine type and veer scenarios. Based on this fundamental understanding, we develop an optimal wind turbine yaw control strategy to maximize turbine power generation under wind veer conditions. The strategy has been tested on individual utility-scale turbines and wind farms, demonstrating up to 3% power gain under large wind veer conditions.   

A Modal Description of Dynamic Wake Meandering

Scans from a nacelle-mounted lidar provide time series wake measurements during three time periods, from which we describe the coherent turbulent structures that contribute to wake meandering through the proper orthogonal decomposition. Subsets of modes are used to make low-order flow field reconstructions in a combinatorial sense, providing more than 30,000 sets of meandering statistics for each case. A regression test using the reconstructed flow statistics identified the modes that contribute most to the accurate description of wake meandering. Spectra were defined from each mode coefficient highlighting the dominant Strouhal number associated with each cohere turbulent structure. The lowest ranking modes do not necessarily contribute most to the accurate representation of wake meandering. Instead, some modes appear to have no influence on meandering dynamics, and still others consistently detract from wake meandering represented in low-dimensional flow reconstructions. No consistent relationship is revealed between characteristic frequencies for each mode and either the inflow or wake measurements, suggesting that a more complex relationship between wake and inflow turbulence may be needed to accurately describe meandering.   

Not Participating

A novel wind energy harvester with no external moving parts was tested at pilot-scale.  The device incorporates a pair of mirrored foils with 1-meter chord and variable heights up to 3-meters, with the foil suction sides facing inward.  When wind flows over the foils, the resulting suction acts on air-jet orifices on the skins of the foils.  The foils themselves are hollow, and the suction pulls air through the center of the foils and out the air-jets.  This air is supplied by intakes at the bottom of the device.  The internal ducted flow can drive an internal turbine-generator.

Two field test campaigns were completed at the Sandia National Laboratories Scaled Wind Farm Technology (SWiFT) site in Lubbock, Texas.  The incoming wind speed and direction was measured at the height of the device.  Variable chokes were placed at the intakes and the velocity and pressure drop was measured across these, providing a measure of mechanical power.

The influence of off-axis wind direction in both low speed (< 5 m/s) and high speed (~ 10 m/s) conditions is shown, demonstrating the ability of the device to align the flow and maintain power extraction without yaw control.  Results are also compared to previous scaled wind tunnel tests and theory.   

Experimentally isolating Coriolis effects on wind turbine wakes in a wind farm in a large-scale rotating platform.

As wind farm footprints grow larger, understanding the interactions between mesoscale physical phenomena, such as Earth's rotation, and large-scale farm wakes become increasingly important. Current field research notes spatial and temporal influences on the global farm wakes caused by Coriolis forces. However, using field experiments to study this is notoriously difficult as there is additional influence from wind veer in the atmospheric boundary layer caused by many factors ranging from terrain to the diurnal cycles. Experiments are performed on a wind farm under the influence of Coriolis forces.  A wind farm is installed in the Coriolis platform at Laboratoire des Écoulements Géophysiques et Industriels. The rotating platform is 13m in diameter and can be filled with water up to 1-meter height. The aim is to isolate the Coriolis influence on the wind farm wakes. The wakes will be measured using large-scale particle image velocimetry. The scaled experiments will contribute to a more comprehensive understanding of the efficiencies and modeling of large-scale wind farms   

Not Participating

Urban wind energy is a sparsely explored option for decentralized renewable energy generation. One of the main issues is the complexity of urban wind resources. The present study addresses this experimentally, exploring the influence of siting on the efficiency of a roof-mounted vertical axis wind turbine of the Savonius (drag) type. Performance and flow field measurements are conducted on a set-up of two aligned cube shaped buildings in a wind tunnel. The position of the wind turbine on top of the buildings is varied, with three positions on each cube respectively. In addition, the effect of freestream turbulence in the inflow generated by an active grid is examined. The flow field is measured both with and without the turbines using particle image velocimetry along the centerline of the buildings, while the torque and rotational velocity of the turbine are captured simultaneously. It is shown that the turbine itself has a substantial impact on the flow field and on the performance. Thus, it is not sufficient to evaluate the available power in an urban environment based only on the flow field without a turbine present. The ideal position of a roof-mounted vertical axis wind turbine will be discussed based on these results.