Bulletin of the American Physical Society
75th Annual Meeting of the Division of Fluid Dynamics
Volume 67, Number 19
Sunday–Tuesday, November 20–22, 2022; Indiana Convention Center, Indianapolis, Indiana.
Session J14: Energy: Wind Power - Offshore, Steering & Coriolis |
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Chair: Michael Howland, Massachusetts Institute of Technology Room: 141 |
Sunday, November 20, 2022 4:35PM - 4:48PM |
J14.00001: Wall-modeled LES of wind-wave-wake dynamics affecting an offshore wind turbine Manuel Ayala, Zein Sadek, Ondrej Fercak, Raul B Cal, Dennice Gayme, Charles Meneveau Offshore wind has the potential to supply a significant proportion of the global electricity use. However, complex flow interactions between the atmospheric boundary layer, the wind turbine array and the ocean can affect the power output and the loading on individual turbines. In order to gain an understanding of the wind-wave-wake dynamics, we perform Large Eddy Simulations of an offshore wind turbine with a moving wave boundary condition to model a monochromatic wave. Drag generated from the interaction of wind with moving waves is modeled using a novel equilibrium moving surface gradient (EMSG) wall model. This EMSG model includes both an equilibrium wall stress that follows the local law-of-the-wall and a moving surface gradient stress. The equilibrium wall stress accounts for momentum loss due to small scale interactions and the latter for momentum loss of a flow that impinges onto an arbitrary surface. The robustness and accuracy of the EMSG wall model is validated against several benchmark cases (flow over moving waves). Comparisons of results from our wall-modeled LES and experiments of a fixed bottom turbine conducted by the PSU Wind Energy and Turbulence lab are discussed. |
Sunday, November 20, 2022 4:48PM - 5:01PM |
J14.00002: Dynamics of Wind, Waves, and Wakes in a Floating Offshore Wind Farm Zein Sadek, Ondrej Fercak, Manuel Ayala, Charles Meneveau, Dennice Gayme, Raul B Cal Floating turbines are subject to hydrodynamic forcing by passing ocean waves, introducing the turbine to six degrees of freedom; leading to potential controls opportunities which can be leveraged to optimize power generation across an array. We analyze experimental data being obtained at the Portland State University (PSU) Wind Energy and Turbulence (WET) lab. Data are generated in a closed-circuit wind tunnel, complemented by a wave tank and particle image velocimetry (PIV) system. A 3x4 model turbine array floating offshore wind plant, installed in the wave tank with spanwise and streamwise spacings of two and six rotor diameters, respectively, will be used for the measurements. A series of vertical-transverse PIV planes will be taken of a single inner-array turbine at increasing downstream locations. An adaptive wave generator, active grid, and series of wind tunnel speeds will be used to generate a variety of waveforms and inflow conditions used to characterize the response of the plant. Results will be used to calculate time-averaged turbulence statistics and quantify the effects of hydrodynamic forcing through phase-averaging of wave position. The results can help provide a fundamental understanding of how coupled wind, wave, and wake dynamics influence floating offshore wind plant performance. Data will be used for comparisons with concurrent LES studies that use a novel surface gradient wall model that accounts for moving bottom surfaces by modifying the surface stress in a time-varying fashion. |
Sunday, November 20, 2022 5:01PM - 5:14PM |
J14.00003: Wall-modeled Large Eddy Simulation of offshore wind turbine wake-wave spectrum interactions Aditya Aiyer, Luc Deike, Michael E Mueller The physics of wind waves play an important role in quantifying momentum transport at the air-sea interface. Significant knowledge gaps exist regarding the coupling between waves, the atmospheric boundary layer, and the operation of offshore wind turbines. This study uses a wall-modeled Large-Eddy Simulation (LES) approach to specify the unsteady wave stress due to a realistic wave field and understand the influence of surface waves on the dynamics of the atmospheric boundary layer and the offshore wind turbine generated wakes. The wave height distribution is calculated using a prescribed JONSWAP wave spectrum to simulate realistic oceanic conditions. The wave model calculates the total drag due to the entire spectrum through a linear superposition of the drag force due to each wave mode accounting for the relative velocity between the wind and the waves. The drag due to the unresolved portion of the wave field is calculated dynamically using a wave kinematics-based model. A variety of sea-state conditions (different spectrum peak characteristics and directional spread) are tested by leveraging the significantly lower computational cost of the wave model. The effect of waves on mean velocity profiles, wave-induced stress, wake meandering, and power production is quantified. |
Sunday, November 20, 2022 5:14PM - 5:27PM |
J14.00004: Computationally Efficient Wave-Modeled Large Eddy Simulation of Finite Offshore Wind Farms Hannah H Williams, Aditya Aiyer, Luc Deike, Michael E Mueller The increasing development of offshore wind, especially on the East Coast of the United States, requires computationally efficient simulation tools that can predict full-scale farm power production. A key coupling in offshore wind farms is the momentum transfer between the marine atmospheric boundary layer and ocean waves. A recently developed sea surface-based drag model is adopted within a Large Eddy Simulation framework to model this interaction combined with an actuator disk model for the wind turbines. This modeling framework is far less computationally intensive than wave phase-resolved approaches but more accurate than wave phase-averaged ones. Additionally, many proposed offshore wind farms on the East Coast are relatively small and are close to the shore where the boundary layer has not fully developed and a traditional streamwise periodic (effectively infinite) framework may not be accurate. The goal of this work is to extend the developed framework to the simulation of finite offshore wind farms to investigate the senstivity of velocity fields and power production to the incoming flow and to ask: do variations in incoming atmospheric turbulence or sea state have a larger influence on the wind farm? |
Sunday, November 20, 2022 5:27PM - 5:40PM |
J14.00005: Sea waves-wind interaction and offshore wind turbine's implications Felice Manganelli, Federico Bernardoni, Stefania Cherubini, Pietro De Palma, Stefano Leonardi Understanding how sea-waves interact with the atmospheric boundary layer is necessary to predict the impact on offshore wind turbines both in terms of power production and loads on the blades. In this study, sea waves are simulated as moving sinusoidal waves. Large Eddy Simulations (LES) are performed with different values of the ratio between wave speed (Uwave) and hub-height wind velocity (Uhub). Four different cases are reproduced with Uwave/ Uhub = [0, 0.4, 0.6, 0.7]. The sinusoidal waves are reproduced in the LES with the Immersed Boundary Method. |
Sunday, November 20, 2022 5:40PM - 5:53PM |
J14.00006: Influence of Coriolis forces on wind turbine wakes in uniform inflow Kirby S Heck, Michael F Howland As larger wind turbines are designed and manufactured, Coriolis forces become increasingly important to the deflection and distortion of turbine wakes in the atmospheric boundary layer. The deflection of turbine wakes impacts the power production of other turbines farther downstream in a wind farm. However, models for wind turbine wakes traditionally neglect or parameterize the effects of Coriolis forces. Large eddy simulations (LES) of an actuator disk model in barotropic, neutrally stratified, uniform inflow are performed over a range of Rossby numbers to vary the Coriolis forcing strength. Wake deflections scale with the inverse of the Rossby number, but lateral pressure gradients are non-negligible in the wake and counteract the Coriolis forcing to reduce wake deflection. To bypass modeling pressure fields for predicting the wake center, the absolute vorticity transport equation is instead used to model the lateral wake velocity. The transfer of planetary vorticity into streamwise and lateral vorticity components creates a counter-rotating vortex pair that induces a lateral velocity inside the wake and causes the wake to distort and curl. The physics presented here are incorporated into a new, physics-based wake model that is compared to LES results. |
Sunday, November 20, 2022 5:53PM - 6:06PM |
J14.00007: Spacing effects on wind turbine array wake development in the presence of Coriolis Natalie V Frank, Martin Obligado, Raul B Cal Wind farm footprints are growing in size, developing large scale global farm wakes. The dynamics of the global farm wakes and the interaction with mesoscale atmospheric phenomena, such as Coriolis forces, becomes increasingly important. Current numerical research indicates that global wind farm wake characteristics can be impacted by Coriolis forces and current field research suggests there are spatial and positional influences on wake characteristics. Experimental studies investigated the influence of Coriolis forces on global wind farm wakes, focusing on the impact of varied downstream turbine spacing and turbine row patterns. Two configurations were tested: Aligned and staggered rows. Experiments were performed on the rotating Coriolis platform at Laboratoire des Écoulements Geophysiques et Industriels (LEGI). The objective of the experiments was to isolate Coriolis influence on the global wind farm wakes of two distinct wind farm layouts. Large scale particle image velocimetry was used to measure the experiments. The scaled experiments contribute to a more comprehensive understanding of the efficiencies and modelling of large-scale wind farms, as well as the layout and configurations of farm design. |
Sunday, November 20, 2022 6:06PM - 6:19PM |
J14.00008: Modeling the effect of wind speed and direction shear on utility-scale wind turbine performance Storm A Mata, Michael F Howland Atmospheric boundary layer (ABL) wind speed and direction shear affect wind turbine power production. Wind farm siting, design, and control strategies should consider time-varying wind shear in the ABL to optimize performance. Wind profiles often exhibit non-monotonic behavior in the stratified ABL, limiting the potential to characterize them with single-parameter models. For example, while daytime mean wind speeds often follow a canonical power law relationship, we show empirically that short-term time-averaged daytime and nighttime conditions are often not well represented with such a model. To characterize the effect of shear on turbine performance, we develop a blade element model that accounts for both speed and direction shear over the rotor. This model computes the inflow speed and angle of attack at each radial and azimuthal position to find the contribution of power for each blade element. We then use this model to predict turbine power production with different combinations of speed and direction shear. The results are compared to simplified models that assume uniform inflow over the rotor area. Finally, using LiDAR measurements as inputs to these models, we qualitatively compare trends in their respective predictions to SCADA field data from utility-scale turbines. |
Sunday, November 20, 2022 6:19PM - 6:32PM |
J14.00009: Analytical modeling of the induction, thrust, and power of a yaw misaligned actuator disk Michael F Howland, Kirby S Heck, Hannah M Johlas Collective wind farm flow control, where individual wind turbines are operated in a suboptimal strategy to benefit the aggregate farm, has demonstrated potential to reduce wake interactions and increase wind farm energy production. However, existing wake models used for control often estimate the thrust and power of yaw misaligned turbines using simplified empirical expressions which require expensive calibration data and do not accurately extrapolate between turbine models. The thrust, velocity deficit, wake deflection, and power of a yawed wind turbine depend on its induced velocity. The induced velocity depends on both the yaw angle and thrust coefficient of the wind turbine. Here, we extend classical one-dimensional momentum theory to model the induction of a yaw misaligned actuator disk. Analytical expressions for the induction, thrust, initial wake velocity deficit, initial transverse velocity, and power are developed as a function of the yaw misalignment angle and the thrust coefficient. The analytical model is validated against large eddy simulations of a yaw misaligned actuator disk over a range of yaws and thrust coefficients. The implications of the developed, predictive model on wake steering, induction control, and joint steering and induction control are discussed. |
Sunday, November 20, 2022 6:32PM - 6:45PM |
J14.00010: Characterizing Spatially Heterogeneous Wind Turbine Wakes Under Yaw and Tilt Misalignment Ryan Scott, Nicholas Hamilton, Raul B Cal The formation of a counter-rotating vortex pair in the wake of a misaligned wind turbine produces a spatially heterogeneous flow with interactions across a range of physical scales. We apply lacunarity analysis to identify the dominant length scales in response to wake deflection and characterize overall flow complexity through a heterogeneity index. Flow data were obtained from large eddy simulations for a single turbine in a neutrally-stable atmospheric boundary layer flow. We considered a range of nacelle misalignment angles including yaw, tilt, and yaw-tilt combinations to parameterize heterogeneity across the full range of possible deflection angles. In addition, we varied roughness height to determine the influence of surface characteristics. Wake flow was isolated from the background by subtracting the boundary layer profile. Spatial heterogeneity was computed from the advection and Reynolds stress budgets at each downstream location. We found the dominant length scales and spatial heterogeneity vary with misalignment in the near wake and are driven by surface interactions in certain cases. Misalignment angles which direct the wake towards the ground experience significant shear which introduces further deformation and compounds heterogeneity from deflection. The streamwise point where these interactions occur is revealed through the heterogeneity index and depends on turbine aspect ratio, misalignment angle, and surface roughness. |
Sunday, November 20, 2022 6:45PM - 6:58PM |
J14.00011: Development of deep learning-based reduced order model for turbine wake control Christian Santoni, Ali Khosronejad, Zexia Zhang, Peter Seiler, Fotis Sotiropoulos Wake interactions between turbines give rise to wind farm power generation losses of 10% to 20%. Although wake interaction can be addressed by increasing the distance between the wind turbines, continuous growth in the scale of turbines may also require an increase in turbine spacing. This may result in wind farms of prohibitive dimensions. Therefore, advanced turbine control such as wake steering with yaw misalignment has been proposed to reduce the distance between turbines and maximize power production. We implemented a reduced-order model capable of predicting the wake redirection and power production of a wind farm. Large eddy simulations of Sandia National Lab scaled wind farm technology (SWiFT) facility at different wind speeds, wind directions, and yaw-misalignment of the wind turbines were used to generate the training/testing datasets. It was shown that the deep learning algorithms accurately predict the velocity field and turbulence kinetic energy in the wake of a yawed wind turbine and the secondary redirection of downwind turbines. |
Sunday, November 20, 2022 6:58PM - 7:11PM |
J14.00012: Wake steering of wind farm over complex terrain Emmanuvel J Aju, Devesh Kumar, Mario A Rotea, Yaqing Jin Wake steering has proven to be effective in increasing the power output of wind farm for aligned wind farms over flat terrains, while our current understanding for its effectiveness over complex terrain remains limited. In this work, systematic wind tunnel experiments were performed to evaluate the performance of an existing wind farm on complex terrain with wake steering. Results show that the variation of yaw angles of upstream turbines effectively deflects the wake flows, which increases the power output of the downstream turbine, especially for the cases with small streamwise gap distances. The maximum wind farm power output can increase up to 9% with the yawing of only first-row turbines in the wind farm. The investigation of wake flow reveals that the complex terrain alters the evolution of wake flow in both streamwise and spanwise directions; this can influence the optimal yaw angle of upstream turbines with the maximum wind farm power output. Complementary measurements for the fatigue loading on turbine tower highlights that the dominating unsteady aerodynamic loads are perpendicular to the rotor surface regardless of incoming flow direction. However, the growth of yaw misalignment mitigates the fatigue loading in the direction perpendicular to rotor. |
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