Flavio Martins
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This study investigates the potential of regenerative wind farming using multirotor systems equipped with paired multirotor-sized wings, termed atmospheric boundary layer control (ABL-control) devices, positioned in the near-wake region of the multirotor. These ABL-control devices generate vortical flow structures that enhance vertical momentum flux from the flow above the wind farm into the wind farm flow, thereby accelerating the wake recovery process. This work presents numerical assessments of a single multirotor system equipped with various ABL-control configurations. The wind flow is modeled using steady-state Reynolds-averaged Navier-Stokes (RANS) computations, with the multirotor and ABL-control devices represented by three-dimensional actuator surface models based on momentum theory. Force coefficient data for the actuator surface models, as well as validation data for the numerical computations, were obtained from a scaled model at TU Delft's Open Jet Facility. The performance of the ABL-control devices was evaluated by analyzing the net momentum entrained from the flow above the wind farm and the total pressure and power available in the wake. The results indicate that, when the ABL-control strategy is employed, vertical momentum flux may become the dominant mechanism for wake recovery. In configurations with two or four ABL-control wings, the total wind power in the wake recovers to 95 % of the free-stream value at positions as early as x/D≈6 downstream of the multirotor system, representing a recovery rate that is approximately an order of magnitude faster than that observed in the baseline wake without ABL-control capabilities. It should be noted, however, that this study employs a simplified numerical setup to provide a proof of concept, and the current findings are not yet directly applicable to real-world scenarios.
In contemporary wind farm design, the primary focus has traditionally been on reducing wake interference to optimize energy capture from horizontal wind flows. However, with the scaling up of wind farms, their interaction with the Atmospheric Boundary Layer (ABL) evolves, making vertical entrainment the main mechanism for the exchange of momentum and energy. This study introduces a methodical approach to augment the efficiency of large-scale offshore wind farms by actively controlling this vertical entrainment of momentum within the ABL. The strategy involves the precise engineering of advection fluxes to alter wind flow dynamics, utilizing turbines as effective vortex generators, toward a process of "regenerative wind farming."This setup aims to create a vorticity and vertical flux system akin to those observed in highly unstable ABLs. Expanding upon previous studies that focused on single Vertical Axis Wind Turbines (VAWTs), our research explores the implementation of multi-rotor systems equipped with lift-generating wings. These systems are designed to exert forces perpendicular to the prevailing wind direction, thus creating trailing vortices and directing the flow orthogonally for improved vertical advection. This research is part of a comprehensive investigative framework that combines experiments and multifidelity simulations. The current study extends those findings to wind farm simulations, aiming to assess the impact of ABL control on a full wind farm scale. The first part of the work validates an established analytical wind farm performance model against real wind farm data for thirty-one wind farms in the North Sea and Baltic Sea. The results confirm the predicted trend of decreased performance with increased wind farm size and density. The model is used to calculate the performance of a wind farm for varying regimes of vertical entrainment due to the creation of large-scale circulatory systems. The results are compared against 3D vortex simulations of the full wind farm in "regenerative wind farming"mode. Our results demonstrate a notable improvement in wind speeds at the turbine hub height and the potential to double the feasible density of wind farms without compromising efficiency compared to traditional setups. These findings suggest a promising pathway towards a more sustainable and profitable future in wind energy, achieved through the strategic manipulation of ABL momentum, regenerating the energy in the wind farm.
This study investigates the near-wake aerodynamics of actuator disks (multirotor devices) paired with lift-generating devices (rotor-sized wings, dubbed ABL-control devices). These rotor-sized wings generate vortical structures that enhance the vertical momentum flux from above the atmospheric boundary layer (ABL) into the wind farm, aiding wake recovery. Using three-dimensional actuator surface models based on Momentum theory, the study employs steady-state Reynolds-averaged Navier-Stokes computations in OpenFOAM to address the current proof-of-concept model. The numerical results of this paper are validated with a comparison against the experimental results of a scaled multirotor device in a wind tunnel. The performance of the ABL-controlling devices is evaluated through the wind farm's total pressure and vertical momentum flux. Results indicate that ABL-control significantly accelerates wake recovery, with designs featuring two or four ABL-control devices achieving 95% total pressure recovery at x/D ≈ 5, one order of magnitude shorter than the baseline setup without ABL-control.
Abstract: In this study, vortical structures are detected on sparse Shake-The-Box data sets using the Coherent-Structure Colouring (CSC) algorithm. The performance of this Lagrangian approach is assessed by comparing the CSC-coloured tracks with the baseline vorticity field. The ability to extract vortical structures from sparse data is accessed on two Lagrangian particle tracking data sets: the flow past an Ahmed body and a swirling jet flow. The effects of two normalized parameters on the identification of vortical structures were defined and studied: the mean track length and the mean inter-particle distance. The accuracy of the vortical-structure detection problem through CSC is shown to improve with decreasing inter-particle distance values, whereas little dependence on the mean track length is observed at all. Overall, the CSC algorithm showed to yield accurate detection of coherent structures for inter-particle distances smaller than 15% of the characteristic dimension of the structure. However, the results quickly deteriorate for sparser Lagrangian data. Graphic abstract: [Figure not available: see fulltext.]