Session A24: Energy: Wind Power

Optimizing the output of wind farms with micro-siting and wake steering: An LES-informed data-driven approach

We present results from an extensive computational campaign focused on maximizing the power output of wind farms. To achieve this objective, we use a framework based on large-eddy simulations of the flow and a Bayesian approach, where the design space is explored with surrogate models. The proposed framework is applied to two problems: layout optimization (micro-siting) and yaw angle optimization (wake steering). We assess the computational feasibility and potential benefits of the proposed method, and compare its performance with conventional optimization strategies. Moreover, we discuss the role of the fluid mechanical phenomena that are neglected by low-fidelity flow solvers but are effectively utilized by the proposed framework to increase the power output of the farms. We find that the proposed framework shows comparable performance to established optimization strategies. However, considerable performance gains can be achieved when the flow is more complex, such as in the case of the wake steering problem, where several of the assumptions in the simplified flow models become less accurate. This work opens up opportunities for data-driven and high-fidelity optimization of wind farms' power output.   

A moving surface drag model for LES of wind over waves with application to offshore wind turbines

Efficiently and accurately representing the complex interactions between wind and waves in large eddy simulations (LES) of the marine atmospheric boundary layer (MABL) is crucial for developing improved climate model parameterizations and for efficient design and operation of offshore wind farms. In this study, we propose a new model, the MOving Surface Drag (MOSD) model for LES, that aims to accurately capture the phase-resolved effects of waves on turbulent airflow, while maintaining computational efficiency. This approach builds upon the surface gradient-based wall model, augmenting it by computing the pressure drag resulting from ideal potential flow interacting with the forward-facing parts of the moving surface, which is approximated as piece-wise ramp flow. Horizontally unresolved waves are modeled with the standard equilibrium wall model. We demonstrate the utility of the model in studying wind-wave interactions by first demonstrating its success in capturing the impact of monochromatic waves on the turbulence statistics for flows over a range of wave conditions through comparisons with experiments, Direct Numerical Simulations (DNS) and wall-resolved LES. Results from application and comparisons with data from a laboratory wind-wave tunnel experiment with a single wind turbine are presented. The results suggest that the use of an LES with the MOSD wall-model provides a cost-effective means to simulate wind-wave interactions in the MABL and in off-shore wind energy applications.   

Analysis of Exergy Destruction in a wind farm with complex terrain

Computational Fluid Mechanics (CFD) has proven to be an instrumental tool in the study of wind behavior in wind farms. While many authors focus on modeling turbines and wind farms in flat topography, complex terrain can impact wind development and power generation efficiency [1]. Exergy is defined as the potential of a system to perform useful work, where irreversibilities such as friction, destroy Exergy and hinder the wind farm’s performance. In this work we perform an Exergy analysis on a wind farm located in a complex topography. The goal is to identify and quantify the irreversibilities of the system resulting from the interaction between the wind, the turbines, and the terrain. We used the commercial software ANSYS Fluent™ to model the fluid mechanics, along with the Actuator Disk model to represent the turbines. We validated our numerical power results with field data from an operative wind farm. The Exergy Destruction is mainly caused by the dissipation of turbulent kinetic energy as a result of the topography’s complexity. The Exergy Destruction contours allow us identifying optimal locations for turbines and can serve as a useful tool for wind farm design.   

Impacts of the near-shore landscape heterogeneity on the off-shore wind turbine efficiency

The efficiencies of off-shore wind farms are often affected by the near-shore landscape exhibiting sharp spatial heterogeneity, which may lead to non-uniformity on the momentum distribution, i.e., the formation of high/low momentum pathways (H/LMPs). To explore this issue, we conduct large-eddy simulations for off-shore wind farms in a neutral atmospheric boundary layer, where the near-shore landscape features spanwise heterogeneity composed of alternating strips of different roughness heights. We vary the off-shore distance (Ls) and explore the effects of H/LMPs on a single off-shore wind turbine at different spanwise locations. Although it is expected that as HMPs and LMPs mix, the momentum magnitude becomes more uniform when spanwise heterogeneity no longer persists in the off-shore region. Our results show that, within a certain range of Ls, the efficiency of the wind turbine in the HMP increases while that of the wind turbine in the LMP decreases as a function of Ls. This behavior is attributed to the decay of secondary flow structures along the streamwise direction in the off-shore region. This finding is crucial for understanding and utilizing the near-shore landscape heterogeneity to enhance the off-shore wind farm efficiency.   

A Modal Description of Dynamic Wake Meandering

Lidar scans from a nacelle-mounted measurement system provide time series of wake measurements during varied atmospheric inflow conditions, from which we describe the coherent turbulent structures that contribute to wake meandering through proper orthogonal decomposition. Subsets of modes are used to make low-order reconstructions in a combinatorial sense, yielding more than 30,000 estimates of meandering for each inflow case. A regression test using the range of reconstructed flow statistics identifies the modes that contribute most to wake meandering. Mode coefficient spectra highlight the dominant Strouhal number associated with each turbulent structure, suggesting that the lowest ranking modes do not necessarily contribute most to the accuracy of the reconstruction. 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 for either the inflow or the lidar measurements, suggesting that a more complex relationship between wake and inflow turbulence may be needed to accurately describe wake meandering.   

Waveform and Turbulence Influence on Wake Morphology Within a Floating Windfarm

The aerodynamic and hydrodynamic forces experienced by floating wind turbines introduce complex dynamics between the turbine and platform orientation, wave conditions, and wake behavior. To maximize the performance of these farms it is necessary to understand the influence each of these factors has on the net behavior. This work conducts a series of particle image-velocimetry (PIV) measurements within a scaled floating windfarm to analyze the coupling behind wind, waves, and wakes. Experiments take place in the Portland State University wind-wave tunnel, equipped with a wave generator, damper, and active grid. Twelve semisubmersible, tri-floater turbines with a rotor diameter of 15 cm are arranged into a farm of four rows. Multiple spanwise-vertical PIV planes are taken downstream of the center turbine in the third row to capture a developed wake within the farm and observe the impact waves have on its morphology. Encoded DC motors in the nacelle of the turbines are used to set the tip speed by varying the resistive load. Multiple waveforms, turbulence intensities, and Reynolds numbers are considered. Mean flow fields and Reynolds stresses are presented, both as ensemble and phase average quantities, to highlight any wave dependence. Resulting data characterize a scaled floating wind farm. Such data is expected to be useful for model development and subsequent optimization strategies for full-size farms.   

Effects of blade fouling on performance of vertical axis wind turbines

Wind energy is seen as one of the most attractive energy sources for the future and has witnessed rapid growth in capacity in recent years; however, it is still facing significant challenges. Harsh weather conditions such heavy rain, sandstorms and wind gusts all negatively impact the turbines’ power production and its life span. Efficiency is reduced through particles contaminating the incoming airflow causing blade fouling, altering surface and mechanical properties of turbine blades. Present study investigates the ramifications of blade fouling affecting various rotor configurations of Vertical Axis Wind Turbines (VAWTs) to reduce and/or prevent the impact of harsh weather on the rotor. This is accomplished through controlled physical experiments recording the torque produced by a rotor which has experienced fouling. Impacts of particles with the blades at various angles of rotor rotation and simulated operating conditions are detected by a high-speed camera system. Particle trajectories prior and after impact are determined with Lagrangian particle tracking techniques and form the basis for design of test blades representing various amounts of fouling. The small-scale nature of the physical experimental models necessitates fine control over torque losses within the testing equipment. Magnetic levitation is introduced aiming to minimise bearing friction along with Eddy Current Braking (ECB) for frictionless speed control of the rotor. Voltage supplied to the ECB is calibrated against the braking force the system is applying for a given rotor angular velocity using wind tunnel tests and verification with a pendulum setup. Information regarding the amount of braking applied is then used in determining the torque said rotor is producing as well as a means for closed-loop speed control. Each component of the test equipment is evaluated individually, recording associated torque losses discretely, permitting a modular configuration of experiment-tailored systems. Allowing the same components to make up systems being tested in a variety of environments such as urban and water-based turbine installations among others. Knowledge obtained in the present experimental campaign then forms the basis for design and optimisation of damage mitigation strategies and systems to be incorporated into VAWTs.    

On the Power Response of Wind Turbines with Hydrostatic Transmission: An Experimental Study

Decarbonizing electricity generation drives the adoption of renewable energies during the energy transition, with wind energy playing a prominent role. Yet, horizontal axis wind turbines pose challenges due to fluctuating wind speeds that create loads on the structure and drivetrain, leading to direct transmission fluctuations. To tackle these issues, hydrostatic transmission integration for wind energy harvesting has seen remarkable growth. This approach offers adaptable gear ratios, allowing variable rotor angular velocity while maintaining constant generator speed. Also, its modularity permits relocating the generator from the nacelle to the ground, reducing torque fluctuations by up to about 40% under turbulent boundary layers. This streamlining of components also leads to significant cost savings in offshore wind turbines' Levelized Cost of Energy (LCOE). The study aims to address a gap in hydraulic wind turbines by characterizing the power output spectrum Φ_P experimentally. For this, two 3-meter diameter horizontal axis wind turbines were deployed in similar flow conditions, and a sonic anemometer assessed the flow structure and statistics at hub height. Initial analysis indicates hydrostatic transmission can effectively reduce high-frequency fluctuations compared to the current configuration. A fraction of these may reduce fatigue loads on the wind turbine and enhance power quality, thereby advancing renewable energy technology.