Wind Turbine Array Research Articles

Analysis of Wind Farms under Different Yaw Angles and Wind Speeds

Wind farm optimization is pivotal in maximizing energy output, reducing costs, and minimizing environmental impact. This study comprehensively explores wind farm behavior under varying wind conditions and yaw angles to achieve these objectives. The primary motivation is to optimize wind farm performance and efficiency through proper yaw adjustment in response to wind speed changes. A computational investigation using a three-by-three wind turbine array was conducted, employing large eddy simulation (LES) to evaluate wind farm performance. Nine LES cases were considered, incorporating three wind speeds (7.3 ms−1, 10.4 ms−1, and 4.3 ms−1) and three yaw angles (30°, 20°, and 0°), with nearly constant turbulence intensity (TI) at 12.0%. The impact of wind speed and yaw angles on wake characteristics and power outputs were analyzed. The findings reveal that wind speed has limited influence on wake characteristics and power outputs, except for lower wind speeds at a yaw angle of 20 degrees. These results contribute to understanding wind farm performance optimization, aiding in developing strategies to enhance energy extraction while minimizing costs and environmental implications.

Offshore construction using gravity-base foundations indicates no long-term impacts on dolphins and harbour porpoise

There are concerns about the short- and long-term effects on cetaceans from offshore construction using pile-driving. Gravity-base foundations and anchored floating turbines are alternative installation methods that may have less impact on cetaceans. In this study, we investigated the response of dolphins (Tursiops truncatus and Lagenorhynchus albirostris) and harbour porpoise (Phocoena phocoena) to the construction of wind turbines using gravity-base foundations off Blyth, Northumberland, United Kingdom using cetacean echolocation recorders (C-PODs). Data were collected at nine sites across 3 years (2016–2018) before, during and after construction. Generalised additive mixed models were used to investigate temporal, environmental, and anthropogenic drivers of dolphin and porpoise occurrence from 143,215 h (5967 days) of C-POD data. The models explained 27% and 30% of the deviance in dolphin and porpoise occurrence, respectively. Overall, the results showed no long-term effect on the dolphin occurrence from the construction of the gravity-base wind turbine array. In contrast, porpoise occurrence increased by 32% and 75%, respectively, in the years during and after construction, compared to the before-construction year. Other predictors of dolphin and porpoise occurrence included month, hour of day, tidal currents and vessel sonar activity. Our findings indicate that wind turbine installation using gravity-base foundations had no long-term effects on the occurrence of dolphins or porpoise and may represent an offshore construction methodology that is less impactful to dolphins and harbour porpoise than impact pile-driven turbine installation methods. These results are important for future offshore energy developments; however, further studies are recommended to investigate potential species and location variations.

An Online Peak Shaving Controller for Optimized Power-Electronic Converter Lifetimes in Turbine Array Generation Systems

Wind and hydrokinetic turbines play an essential role in the transition to carbon-free electricity generation, and improving the economics of turbine systems can accelerate this change. Recognizing that operational costs represent a significant share of the total generation costs, researchers have proposed methods for optimizing the turbine system maintenance while considering the impact of power-electronic converter lifetime on the maintenance costs. This work considers how peak-shaving can be applied to turbine units across an array to exchange energy generation for prolonged power-electronic converter lifetimes and reduced maintenance visits. This work proposes an online peak shaving controller (PSC) that finds the optimal peak-shaving actions by minimizing a function of the predicted levelized cost of energy (LCOE). This real-time minimization of LCOE via a model predictive control style framework ensures the PSC is economically beneficial to the system. The PSC simulates the turbine system with different peak-shaving actions over a prediction horizon, then calculates LCOE considering the power-electronic converter lifetimes and turbine array energy generation. A hardware test demonstrates the real-time peak-shaving action leveraged by the PSC, while a simulation case study for a wind turbine array demonstrates the economic benefit offered over the array's full lifecycle.

Hybrid Water Pumping Control System for Irrigation using Arduino

Abstract: There are many water pumping system such as diesel powered, solar photovoltaic, mechanical windmill exists. Few combine solar and wind energy sources to provide better performance and reliability to the existing system. In this paper wind turbine and solar photovoltaic (PV) water pumping array are analyzed separately and are combined as a hybrid system. Large amount of water pumped from the water resources are not effectively used. So a suitable control methodology was also proposed to operate the pump automatically depending on the water availability and the water requirement for crops .The main objective is to provide 1.Advantage of hybrid system over WT or solar PV array separately.2.suitable methodology to prevent water loss. Additionally MPPT system Can be used to improve the efficiency of PV array

Uncertainty quantification analysis for simulation of wakes in wind-farms using a stochastic RANS solver, compared with a deep learning approach

Quantification of uncertainties in Reynolds–Averaged Navier–Stokes (RANS) simulations has gained a considerable interest in turbulence modeling. We present two different approaches for the quantification and propagation of model-form and operational uncertainties in context of wind turbine RANS simulations. The first approach is based on a stochastic RANS solver in OpenFOAM using intrusive polynomial chaos method (Parekh and Verstappen, 2023). Here the uncertainties are propagated through a single (large) simulation for the coupled coefficients of the polynomial expansion. The second approach is a surrogate based uncertainty quantification (SBUQ) method. The surrogate model comprises of a 3D U-Net neural network (trained over a single wind turbine) combined with a wake superposition model in order to the prediction of flow field in an array of wind turbines. The above-mentioned approaches are applied for uncertainty quantification analysis in RANS simulations of two turbulent engineering flow problems — (i) a wake past a single wind turbine, and (ii) wake interactions and power losses in an array of wind turbines. The results show that the uncertain RANS solutions from the two approaches are able to reasonably capture the reference high-fidelity solution. We also discuss comparisons between the two approaches including computational cost, applicability, generality etc. The two methods can be further explored and applied to engineering applications where it is critical to compute the turbulent RANS solution in presence of various sources of uncertainties.

Power Production and Blade Fatigue of a Wind Turbine Array Subjected to Active Yaw Control

This study investigated the power production and blade fatigue of a three-turbine array subjected to active yaw control (AYC) in full-wake and partial-wake configurations. A framework of a two-way coupled large eddy simulation (LES) and an aeroelastic blade simulation was applied to simulate the atmospheric boundary layer (ABL) flow through the turbines and the structural responses of the blades. The mean power outputs and blade fatigue loads were extracted from the simulation results. By exploring the feasible AYC decision space, we found that in the full-wake configuration, the local power-optimal AYC strategy with positive yaw angles endures less flapwise blade fatigue and more edgewise blade fatigue than the global power-optimal strategy. In the partial-wake configuration, applying positive AYC in certain inflow wind directions achieves higher optimal power gains than that in the full-wake scenario and reduces blade fatigue from the non-yawed benchmark. Using the blade element momentum (BEM) theory, we reveal that the aforementioned differences in flapwise blade fatigue are due to the differences in the azimuthal distributions of the local relative velocity on blade sections, resulting from the vertical wind shear and blade rotation. Furthermore, the difference in the blade force between the positively and negatively yawed front-row turbine induces different wake velocities and turbulence distributions, causing different fatigue loads on the downwind turbine exposed to the wake.

Study of Vertical-Axis Wind Farm Layouts Using a 2D Actuator-Cylinder RANS Model

The actuator-cylinder RANS (Reynolds-averaged Navier-Stokes equations) model was used to study the performance of two different arrays of wind turbines. The staggered array proved to be more efficient than the fish-school array (grouped in pairs) in most directions; however, the fish-school array outperformed the conventional staggered array when the pairs of turbines were facing the wind. Increases in global power coefficient up to 16% were found when the wind speed was 8 ms-1 and up to 10% when the wind speed was 10 ms-1. Despite the fish-school array being slightly less efficient, this array yielded almost twice as much power density as the staggered array in almost all directions. The current methodology proves to be a fast tool for the estimation of vertical-axis wind turbine farms compared to full RANS simulations.

Interaction between heterogeneous thermal stratification and wakes of wind turbine arrays

AbstractThe thermal heterogeneity between the land and sea might affect the wind patterns within wind farms (WF) located near seashores. This condition was modeled with a large‐eddy simulation of a numerical weather prediction model (Weather Research and Forecasting) that included the wind turbine actuator disk model (ADM). The assumed condition was that the downstream surface temperature was relatively higher (unstably stratified condition) than the neutrally stratified upstream wind. Under this condition, a thermal internal boundary layer (TIBL) was developed from an area where a step‐changed surface temperature was implemented. The combined effect of the wake deficit due to the WF and velocity recovery as a result of enhanced mixing under unstable stratification showed significant modulation of the wind speed at the hub height when local atmospheric stability affected the wind turbine (WT). We show that TIBL height depends on the variables to be evaluated as the threshold. A precise prediction of the TIBL height is beneficial for better estimation of power generation. A prediction model was proposed as an extension of the internal boundary layer (IBL) model for neutral stratification, and the results tracked TIBL development reasonably well. The effects of WFs on surface properties (e.g., friction velocity, heat flux, and Obukhov length) and the tendency of IBL growth were minor. A single WT wake was also assessed under several TIBL developmental stages (i.e., location) and thermal stratification conditions. The standard deviation of the wake deficit increased vertically during the development stage of the TIBL. In contrast, the coefficients in the horizontal and vertical directions were comparable when the WT was deep inside the TIBL.

Large-eddy simulation of a wind-turbine array subjected to active yaw control

Abstract. This study validates large-eddy simulation (LES) for predicting the flow through a wind turbine array subjected to active yaw control. The wind turbine array consists of three miniature wind turbines operated in both non-yawed and yawed configurations under full-wake and partial-wake conditions, for which wind tunnel flow measurements are available. The turbine-induced forces are parametrised by three different models: the standard actuator disk model (ADM-std), the blade element actuator disk model (ADM-BE), also referred to as the rotational actuator disk model (ADM-R), and the actuator line model (ALM). The time-averaged turbine power outputs and the profiles of the wake flow statistics (normalised streamwise mean velocity and streamwise turbulence intensity) obtained from the simulations using the ADM-std, the ADM-BE and the ALM are compared with experimental results. We find that simulations using the ADM-BE and ALM yield flow statistics that are in good agreement with the wind-tunnel measurements for all the studied configurations. In contrast, the results from LES with the ADM-std show discrepancies with the measurements obtained under yawed and/or partial-wake conditions. These errors are due to the fact that the ADM-std assumes a uniform thrust force, thus failing to capture the inherently inhomogeneous distribution of the turbine-induced forces under partial wake conditions. In terms of power prediction, we find that LES using the ADM-BE yields better power predictions than the ADM-std and the ALM in the cases considered in this study. As a result, we conclude that LES using the ADM-BE provides a good balance of accuracy and computational cost for simulations of the flow through wind farms subjected to AYC.

A simple method of fast evaluating full-field wake velocities for arbitrary wind turbine arrays on complex terrains

Wind energy is an important option of renewable energy and plays more and more an irreplaceable role in many regions. A technical and meanwhile a scientific problem directly relevant to selecting the wind farm site, optimizing the wind farm layout and evaluating the power output, is to calculate accurately the wake effects generated behind wind turbines, which affect the wind velocity distribution of downstream turbines and reduce the power output of a wind farm. Through modifications of near-field and far-field empirical wake models and the wake model on a complex terrain, a unified wake model is developed to calculate the full-field wake velocity distribution over a wind farm with arbitrary turbine arrays located on flat or complex terrains. The derived wake velocity is formulated in an explicit and concise form to obtain the wind velocity at any position within the turbine arrays. The velocity distribution over the whole array can be fast acquired by implementing a simple procedure and occupying the least computing resources. Compared to the CFD modelling, the present method performs superiorly in both easiness and efficiency, which would be a powerful tool in designing and optimizing a large wind farm composed of numerous and variably deployed turbines of different densities on complex terrains. With this solution, it becomes feasible to construct the wind turbine arrays at the sites of restricted space, specifically the offshore islands and the large floating structures.

Investigation of the combined influence of arrangement and configuration parameters on the performance of vertical axis wind turbines in staggered arrangements

Vertical-axis wind turbine (VAWT) array has attracted much attention due to its higher power density, but existing studies put little emphasis on the configuration parameters of one VAWT in array. Thus, a comprehensive study was carried for the combination effect of arrangement and configuration parameters on the aerodynamic performance of two VAWTs in staggered arrangements. Mutual influence of two turbines under different relative arrangement angles (θ), turbine spacing, blade pitch angles (BPA), and tip speed ratios of the downstream turbine were investigated. A major finding is that the location of the downstream VAWT can be divided into two regions with θ = 60° as the turning point, where the regular patterns of the average power coefficient of double VAWTs (CP,avg) with BPA are different. When the downstream turbine is located in the high-speed zone (θ ≤ 60°), positive BPAs benefit the performance of turbines, and 2.5° is the general optimal BPA. While for the case of downstream VAWT in the wake region (θ > 60°), the optimal BPA is a variable related to turbine spacing. Compared with the zero pitch blade, the maximum CP,avg can increase by 7.3% at most (in the 2D-75° case). Flow characteristic analysis indicated that the trigger of the dynamic stall and the wake interaction is the main reasons for different operation features of staggered arrangements.

Numerical Investigation of the Influence of the Wake of Wind Turbines with Different Scales Based on OpenFOAM

The wake of a wind turbine has an important influence on the output power of wind farms. Staggered height layout is an emerging method for the layout optimization of wind farms. In order to study the effect of a staggered height layout on the overall power output of wind farms in depth, we established a combination of two large wind turbines and three small wind turbines arranged laterally between the two large wind turbines, and set four working conditions with different distances between the small wind turbines and the downstream large wind turbines as the research objects. The wind turbine array is analyzed by numerical simulation The layouts add three small wind turbines between the two large wind turbines, and each row of small wind turbines has a different distance from the downstream large wind turbines. The results show that as the distance from the upstream large wind turbine increases, the power of the three small wind turbines on the downstream wind turbine tends to be positive. The numerical simulation suggests that under the inflow wind speed, the closer to the downstream large wind turbine, the higher the wind speed is at the hub height.

Analytical model of fully developed wind farms in conventionally neutral atmospheric boundary layers

The wind energy industry relies on computationally efficient engineering-type models to design wind farms. Typically these models do not account for the effect of atmospheric stratification in either the boundary layer or the free atmosphere. This study proposes a new analytical model for fully developed wind-turbine arrays in conventionally neutral atmospheric boundary layers frequently encountered in nature. The model captures the effect of the free-atmosphere stratification, Coriolis force, wind farm layout and turbine operating condition on the wind farm performance. The model is developed based on the physical insight derived from large-eddy simulations. We demonstrate that the geostrophic drag law (GDL) for flow over flat terrain can be extended to flow over fully developed wind farm arrays. The presence of a vast wind farm significantly increases the wind farm friction velocity compared with flow over flat terrain, which is modelled by updated coefficients in the GDL. The developed model reliably captures the vertical wind speed profile inside the wind farm. Furthermore, the power production trends observed in simulations are reliably reproduced. The wind farm performance, normalized by the geostrophic wind speed, decreases as the free-atmosphere thermal stability increases or the Coriolis force decreases. In addition, we find that the optimal wind farm performance is obtained at a lower thrust coefficient than the Betz limit, which indicates that optimal operating conditions for turbines in a wind farm are different than for a single turbine.

Collective wind farm operation based on a predictive model increases utility-scale energy production

In wind farms, turbines are operated to maximize only their own power production. Individual operation results in wake losses that reduce farm energy. Here we operate a wind turbine array collectively to maximize array production through wake steering. We develop a physics-based, data-assisted flow control model to predict the power-maximizing control strategy. We first validate the model with a multi-month field experiment at a utility-scale wind farm. The model is able to predict the yaw-misalignment angles which maximize array power production within ± 5° for most wind directions (5–32% gains). Using the validated model, we design a control protocol which increases the energy production of the farm in a second multi-month experiment by 3.0% ± 0.7% and 1.2% ± 0.4% for wind speeds between 6 m s−1 and 8 m s−1  and all wind speeds, respectively. The predictive model can enable a wider adoption of collective wind farm operation. Individual operation of turbines in wind farms results in energy losses from wake interactions. Here Howland et al. report on an experimentally validated model to implement collective operation of turbines, which increases the farm’s energy production.

Experimental Modelling of Point-Absorber Wave Energy Converter Arrays: A Comprehensive Review, Identification of Research Gaps and Design of the WECfarm Setup

Commercial wave energy exploitation will be realised by placing multiple wave energy converters (WECs) in an array configuration. A point-absorber WEC consists of a floating or submerged body to capture wave energy from different wave directions. This point-absorber WEC acts as an efficient wave absorber that is also an efficient wave generator. Optimising the WEC array layout to obtain constructive interference within the WEC array is theoretically beneficial, whereas for wind farms, it is only important to avoid destructive interference within an array of wind turbines due to wake effects. Moreover, the WEC array layout should be optimised simultaneously with the applied control strategy. This article provides a literature review on the state of the art in physical modelling of point-absorber WEC arrays and the identification of research gaps. To cover the scientific gap of experimental data necessary for the validation of recently developed (nonlinear) numerical models for WEC arrays, Ghent University has introduced the “WECfarm” project. The identified research gaps are translated into design requirements for the “WECfarm” WEC array setup and test matrix. This article presents the design of the “WECfarm” experimental setup, consisting of an array of five generic heaving point-absorber WECs. The WECs are equipped with a permanent magnet synchronous motor (PMSM), addressing the need for WEC array tests with an accurate and actively controllable power take-off (PTO). The WEC array control and data acquisition are realised with a Speedgoat Performance real-time target machine, offering the possibility to implement advanced WEC array control strategies in the MATLAB-Simulink model. Wave basin testing includes long- and short-crested waves and extreme wave conditions, representing real sea conditions. Within the “WECfarm” project, two experimental campaigns were performed at the Aalborg University wave basin: (a) a testing of the first WEC in April 2021 and (b) a testing of a two-WEC array in February 2022. An experimental campaign with a five-WEC array is under preparation at the moment of writing.

Power and Flow Analysis of Axial Induction Control in an Array of Model-Scale Wind Turbines

As research on wind energy has progressed, it has broadened from a focus on the wind turbine to include the entire wind farm. In particular, methods to mitigate the negative effects of upstream wakes on downstream turbines have received significant attention. One such mitigation method is axial induction control (AIC) in which upstream turbines are derated to reduce the momentum deficits in their wakes, leaving higher speed flow for downstream turbines. If performed correctly, it is theorized that the power production gains in downstream turbines can compensate for the power sacrificed by derating upstream turbines. Previous work has indicated that the “excess” energy left in the wake of the derated turbine is along the edges of the wake such that a turbine placed directly downstream will see little to no increase in power. To address this hypothesis, we performed a control and treatment experiment with model-scale turbines in a wide flume. Five turbines were arranged in three successive streamwise rows, with the first two rows consisting of two aligned turbines, while three turbines with small transverse spacing were placed in the third row, the central of which was also streamwise-aligned with the upstream two turbines. This arrangement was used to evaluate the difference in power production primarily among the turbines in the third row when the upstream turbines were derated. Particle image velocimetry (PIV) was used to measure the wake in the streamwise-vertical planes along the centerline of the array and along the rotor tips of the centerline turbines between all rows, and high accuracy power measurements were recorded from each turbine. The results show that the total power of the array was decreased while implementing AIC but that individual turbine performance differed from predictions. PIV results show that mean kinetic energy (MKE) is redistributed to the edges of the wakes as has been previously hypothesized. We provide an analysis of the results that connects both the power and flow measurements and that highlights several of the aspects of wind turbine wake flows that make them so complex and challenging to study.

Velocity data in a fully developed experimental wind turbine array boundary layer

AbstractExperimental data are reported for a wind turbine array boundary layer (WTABL) in a model wind farm. An array of 95 model wind turbines consisting of 5 streamwise columns by 19 spanwise rows was studied in a high Reynolds number boundary layer in the Flow Physics Facility (FPF) at the University of New Hampshire. The wind turbine array was constructed of porous disks of 0.25 m diameter, which were drag (thrust) matched to typical offshore wind turbine operating conditions. The turbine spacing was 8 diameters in the streamwise and 4 diameters in the spanwise directions. Spires were used to thicken the boundary layer and achieve a boundary layer thickness on the order of 1 m at the first row of the wind turbine array, which is located 33 m downstream from the test section inlet, thus placing the turbines in the bottom 1/3 of the boundary layer. Velocity profiles were measured with a pitot tube in the center column of the array. To within experimental uncertainty, a fully developed WTABL condition is observed in the mean velocity, for defined inlet conditions and spacings, from row 12 on. The wind turbine array acts as a sparse displaced roughness: it creates an internal layer whose origin (in the wall‐normal direction) remains fixed in space, while the turbulent boundary layer the array was placed in continues to grow. Careful consideration was given to an expanded uncertainty analysis, which elucidates the need for long measurement times in large facilities. Porous disk turbine models are the experimental equivalent of numerical actuator disks; therefore, this publicly available data set is expected to be useful for numerical model validation.

Effect of Floating Offshore Wind Turbines on Atmospheric Circulation in California

In California offshore waters, sustained northwesterly winds have been identified as a key energy resource that could contribute substantially to California’s renewable energy mandate. It is these winds that drive upwelling, which is responsible for much of the primary productivity that sustains one of the richest ecosystems on the planet. The goal of this study is to quantify changes in wind fields at the sea surface as the result of offshore wind turbine deployments by use of an atmospheric model. Modeled wind fields from this study will drive an ocean circulation model. The Weather Research and Forecasting model was implemented on a regional scale along the U.S. west coast, with a higher resolution nest along the California continental shelf. Simulated arrays of offshore wind turbines were placed within call areas for wind farm development offshore of Central and Northern California. At full build-out, it was found that wind speeds at 10 m height are reduced by approximately 5%, with wakes extending approximately 200 km downwind of the nominated lease block areas. The length scale of wind speed reductions was found to be several times the internal Rossby radius of deformation, the spatial scale at which rotationally-influenced ocean circulation processes such as upwelling occur.

Development of an integrated solar and wind driven energy system for desalination and power generation

Energy and water are clearly recognized by people as two primary life-sustaining commodities. In terms of current global environmental initiatives, it is important to provide them both in a nature-friendly manner. This study develops a new renewable-based integrated energy system for power generation and desalination and investigates it specifically for Antigua and Barbuda, a Caribbean island nation, to reduce the region’s reliance on a volatile and polluting fossil fuel-based energy infrastructure. Solar and wind, abundantly available in the region, are considered and utilized as the two energy sources enabling electricity and potable water production in a nature-friendly manner. The excess power generated by photovoltaic solar panels and wind turbine arrays is mechanically stored by compressing air into off-shore underwater balloons to provide a reliable renewable-based energy infrastructure for Antigua and Barbuda. The system’s performance is investigated energetically and exergetically by using thermodynamic approaches. In this regard, it is evaluated that the proposed system is capable of operating with energy and exergy efficiencies of 45.4% and 37.6%, respectively. The system’s annual electricity production is evaluated as 316 GWh corresponding to 102.6% of annual electricity requirement of Antigua and Barbuda. In addition, the system supplies 124 tons of fresh water on a daily-basis and compressed air to fuel 140 short-range (80 km) pneumatic vehicles. It is, furthermore, found that potential system implementation can reduce greenhouse gas emissions in the region by 88%.

On the impact of layout in the dynamics of wind turbine arrays under passive oscillations

Laboratory experiments were performed to explore the layout effect on multiscale motions of wind turbines that are able to oscillate passively and the impact on power output fluctuations, which is instrumental toward understanding the dynamics of floating turbine arrays. We studied 3 × 3 and 3 × 5 turbine arrays in aligned and staggered configurations with inter-row separations of Sx/dT=5 and ten sharing transverse spacing of Sy/dT=2.5. A three-axis accelerometer characterized turbines' oscillations, whereas the power output was obtained directly. Particle image velocimetry was used to monitor eventual flow irregularities. The standard deviation of pitch angle, Ap(°) about the equilibrium, obtained from direct integration of instantaneous angular velocity, shows that the turbines underwent relatively small-amplitude pitch motions with maximum intensity that monotonically decreasing with increasing row location in the aligned layout. However, this was not the case in the staggered configurations; indeed, the second row of turbines underwent larger pitch amplitude in the Sx/dT=10 case. Flow channeling and larger turbine spacing promote the development and entrainment of large coherent motions producing larger unsteady forcing and triggering enhanced turbine motions. The instantaneous pitching angle density distribution exhibited Gaussian-like distribution irrespective of the units' location. A formulation for turbine pitching motions based on the balance between wind load restoring force and gravity shows that the bulk natural frequency modulates the turbine pitching angular velocity. The variation in turbine pitching amplitudes was similar to those of the mean power output. The power output spectra evidenced modulation of the local turbulence and turbine pitching natural frequency due to the flow-induced turbine pitching motions.