Performance Of Downstream Turbines Research Articles

Influence of wakes interaction and upstream turbulence on three tidal turbines behaviour

The current study presents numerical results on three tidal turbine models (two in front, one downstream) interacting in a turbulent upstream flow. The numerical results come from a lifting-line (LL) embedded in a Lagrangian vortex particle (VP) solver: Dorothy LL-VP. The objective is to assess the extent to which this numerical tool is suited to reproduce accurately wakes interaction as well as fluctuating loads perceived by the downstream turbine. To this aim, the numerical set-up reproduces an experimental campaign led at IFREMER’s wave and current flume tank. The downstream turbine is placed at different positions to change the wakes interaction. Two upstream turbulence intensities (TI) experimentally tested are reproduced numerically using the synthetic eddy method (SEM). Favourable comparisons are obtained between numerical and experimental wakes, including velocity profiles. Preliminary results suggest that the downstream turbine performance decrease is numerically well captured. More investigations are needed on the loads fluctuations with longer computation time, and adding an angular velocity controller as well as hub modelling to Dorothy LL-VP.

Investigation of tidal turbine array performance using computational fluid dynamics in the presence of waves

Tidal turbine arrays have undergone extensive research to determine the optimal spacing for efficient performance and reduced wake generation. Small-scale laboratory tests are typically conducted to analyze wake structures prior to deployment. These tests often result in conditions of extreme blockage due to channel narrowing in comparison to turbine size. The primary objective of this study is to investigate flow behavior around turbines under blockage conditions and their performance close to the free surface, both in current-only and wave-and-current scenarios. The methodology employed a combination of blade element momentum theory and computational fluid dynamics (CFD) integrating a virtual blade model (VBM) code. The findings of this study indicate potential enhancements in tidal turbine array performance of up to 7% in lateral arrangements and 11% in streamwise arrangements under blockage conditions. The wake is significantly influenced by surface waves, which also contribute to increased downstream turbine performance.

A Reinforcement Learning framework for Wake Steering of Wind Turbines

Ideally, optimum power for a single turbine is obtained when the wind-turbine is aligned with the wind direction. However in multi-turbine wind-farm set-up, wake effects lead to decreased power production from downstream turbine [1, 2, 3, 4, 5]. Hence, a control strategy based on wake steering involves misalignment of upstream turbines with the wind direction causing their wakes to deflect away from downstream wind turbines needs to be investigated. A great deal of work has been put into dynamically controlling the orientation of the individual wind turbines to maximize the power output of the farm [6, 7, 8, 9]. In the wake-steering based control, the misaligned wind turbines produce less power, while the performance of downstream turbines gets enhanced which increases overall net power gain for the wind power plant. Traditionally, the benefits of wake steering have been demonstrated assuming fixed wind directions (e.g., using high-fidelity modeling). Amongst the most recent techniques, particularly promising is the use of Reinforcement learning (RL), which is a branch of machine learning where models are trained to make decisions based on observations of their environment. It is a flexible framework for devising strategies for solving optimal control problems in a broad range of applications across the sciences. Early attempts at using Reinforcement learning for wake steering have been carried out [7, 8, 9], and show promising results. In practice, however, wake-steering controllers must operate in dynamic wind environments in which the wind conditions are estimated from imperfect measurements. Hence, a reinforcement learning framework is developed in this work for dynamic wind conditions. The results show that the framework is promising, and we compare the deep reinforcement learning approach against a considerably more expensive traditional optimization approach which serves as a good baseline. Future work could include looking at more realistic wake models, steering in the presence of noisy observations, and incorporating weather predictions.

An analytical double-Gaussian wake model of ducted horizontal-axis tidal turbine

The wake development of a tidal turbine should be fully considered in the array arrangement. There are many studies on wake characteristics, mainly focusing on a conventional horizontal-axis turbine, while a ducted turbine has attracted little attention. This paper investigates the wake characteristic of a ducted turbine using flume experiments and large eddy simulations. An analytical wake model of the ducted turbine is proposed and verified by the wake profile under different inflow velocities and the downstream turbine performance under different tandem arrangements. The results show that a ducted turbine wake still maintains a high self-similarity, and the wake profile is approximately the double-Gaussian curve. Compared with a conventional tidal turbine, a ducted turbine has a faster wake recovery speed, but a larger radial influence range. Therefore, ducted turbine arrays should be configured with wider radial distances and shorter axial distances.

The effect of vertical arrangement on performance and wake characteristics of two tandem offshore wind turbines under various operating conditions

Apart from streamwise and lateral distances, a vertical distance may also be imposed for adjacent wind turbines to achieve performance improvement of downstream turbines. Previous research was primarily devoted to wind farm layout optimisation using simplified analytical wake models, while impacts of operating conditions were ignored for studies using more advanced Large-Eddy Simulation (LES) methods. In this paper, the effect of vertical arrangement on performance and wake characteristics of two tandem offshore wind turbines under various operating conditions is investigated using an LES approach coupled with an actuator line technique. Results show that vertically arranging turbines can improve downstream turbine performance, but its effects vary with the operating conditions. If turbines typically operate below or at the rated condition, due to deflection of upstream turbine wake associated with shaft tilt, raising the upstream turbine can result in greater improvement in power output, with a considerable rise of 50% for a relatively small height difference of 0.1 times rotor diameter. For above-rated operating conditions, the wind shear effect becomes important and it is preferable to increase the hub height of the downstream turbine to take advantage of higher wind speed. Wake characteristics of both turbines are analysed to support the results.

Optimal Control for Wind Turbine Wake Mixing on Floating Platforms

Dynamic induction control is a wind farm flow control strategy that utilises wind turbine thrust variations to accelerate breakdown of the aerodynamic wake and improve downstream turbine performance. However, when floating wind turbines are considered, additional dynamics and challenges appear that make optimal control difficult. In this work, we propose an adjoint optimisation framework for non-linear economic model-predictive control, which utilises a novel coupling of an existing aerodynamic wake model to floating platform hydrodynamics. Analysis of the frequency response for the coupled model shows that it is possible to achieve wind turbine thrust variations without inducing large motion of the rotor. Using economic model-predictive control, we find dynamic induction results that lead to an improvement of 7% over static induction control, where the dynamic controller stimulates wake breakdown with only small variations in rotor displacement. This novel model formulation provides a starting point for the adaptation of dynamic wind farm flow control strategies for floating wind turbines.

Research on the tandem arrangement of the ducted horizontal-axis tidal turbine

Array research of tidal turbine is critical to make it cost-effective and commercializing. There are many studies of turbine arrays, which mostly focus on a conventional horizontal-axis turbine. While a ducted turbine is also available for commercial application, which draws little attention. In this paper, the tandem arrangement of ducted horizontal-axis turbines is studied based on the flume experiment and the large eddy simulation (LES). The turbine's performance changes are investigated under the 5-15D (D represents the turbine diameter) tandem distance. Research results show that the downstream turbine's performance degrades significantly, and its efficiency drops to roughly half of the upstream turbine when the tandem distance is 5-10D. When the distance increases more than 10D, the downstream turbine performance can reach 80% of the upstream turbine. As the distance increases, this performance recovery becomes less significant. In terms of load fluctuation, with the interaction of the upstream wake and the surrounding flow field, a spiral oscillation wake region will be formed about 10D behind the upstream turbine. Therefore, with the increase of the tandem distance, the load fluctuation of the downstream turbine does not gradually decrease as a result. This fluctuation is more than twice that of the upstream turbine, and the maximum can reach 5 times.

Investigation of Tidal Turbine Array Performance Using Computational Fluid Dynamics in the Presence of Waves

Tidal turbine arrays have been widely investigated to find the optimum spacing for the efficient performance and less wake generation. Small scaled laboratory tests are usually performed to analyze the structure of wakes prior to the deployment. These tests result in extreme blockage conditions due to the narrowing of channels compared to size of turbines. The main aim is to investigate the behavior of flow around the turbines in blockage conditions and the performance of turbines closed to the free surface in current-only and wave-and-current scenarios. The methodology was based on blade element momentum and computational fluid dynamics approach with the integration of virtual blade model code. The results of this work indicate that the performance of tidal turbine array can be enhanced by up to 7% in blockage conditions in lateral arrangement and 11% in stream wise arrangement. The wake is highly influenced by the surface waves that also increase the performance of downstream turbines.

Prediction of power generation of two 30 kW Horizontal Axis Wind Turbines with Gaussian model

In order to improve the total efficiency of power generation in a wind farm, this paper investigated the effect of different operating conditions of the upstream wind turbine on the power of the downstream wind turbine by Gaussian wake model. A three-bladed Horizontal Axis Wind Turbine with the generator capacity of 30 kW was used. Firstly, Gaussian model for evaluating the wake flow was developed, which fit well with experiment data. Then, the influence of the operating condition of the upstream turbine on the downstream turbine performance was estimated by calculating the energy amount resulted from the velocity deficit of the wake. Finally, the effect of the installation position of the downstream wind turbine was analyzed. In consequence, the total power coefficient Ptotal of the wind turbines was relatively higher when the upstream turbine was at tip speed ratio λ = 6.4 and pitch angle β = 2° among different test conditions. Meanwhile, the Ptotal showed the maximum value when the downstream turbine was installed at the streamwise location x/D = 2.0 and lateral offset location y/R = 1.5 when the inflow turbulence intensity is 0.22≤TIref ≤ 0.35. This paper provided a better guidance for optimizing the wind turbine layout and improving the total power output of the entire wind farm.

A numerical study on the interaction between two cross-flow turbines in tandem configuration to support a simplified turbine model approach

In the planning of hydrokinetic turbine array deployment and for the performance prediction of its constituent turbines, the use of simplified turbine models is essential to alleviate the computational costs. The Effective Performance Turbine Model (EPTM) introduced in 2018 is a promising tool for that purpose, allowing array analysis and optimization. Its performance predictions scale with a local flow velocity characterization, which ensures to take into account inherently blockage effects and mean, local flow conditions. However, the characteristics of the local flow within an array also include different types of perturbation such as shear, large-scale temporal fluctuations, and turbulence. To ensure that the model is still reliable in those conditions, this paper presents a validation of the EPTM through the analysis of a large-scale tandem turbine configuration. In fact, three unsteady-Reynolds-averaged-Navier–Stokes simulations of a cross-flow turbine tandem configuration with a longitudinal spacing of six diameters have been conducted in this study, in addition to a simulation of a single turbine with turbulent ambient conditions. This set of simulations allows us to study independently the different types of perturbations associated with array deployment. Whereas the slow-varying large-scale upstream velocity fluctuations do not seem to affect significantly the turbine operation, the upstream non-uniform velocity distribution affects appreciably the extracted power. We find also that the value of the effective power coefficient associated with the EPTM needs to be adapted to the array simulation. Compared to the case of a single turbine in a uniform flow with a low turbulence level, we show that a smaller effective power coefficient value must be used in array simulations. An important result is that the different types of perturbations are found to yield similar effective performance coefficients, which suggests that the same set of values can be used throughout the array. With the appropriate set of values, we show that the EPTM succeeds to predict accurate downstream turbine performance.

Aerodynamically Interacting Vertical-Axis Wind Turbines: Performance Enhancement and Three-Dimensional Flow

This study examined three-dimensional, volumetric mean velocity fields and corresponding performance measurements for an isolated vertical-axis wind turbine (VAWT) and for co- and counter-rotating pairs of VAWTs with varying incident wind direction and turbine spacings. The purpose was to identify turbine configurations and flow mechanisms that can improve the power densities of VAWT arrays in wind farms. All experiments were conducted at a Reynolds number of R e D = 7.3 × 10 4 . In the paired arrays, performance enhancement was observed for both the upstream and downstream turbines. Increases in downstream turbine performance correlate with bluff–body accelerations around the upstream turbine, which increase the incident freestream velocity on the downstream turbine in certain positions. Decreases in downstream turbine performance are determined by its position in the upstream turbine’s wake. Changes in upstream turbine performance are related to variations in the surrounding flow field due to the presence of the downstream rotor. For the most robust array configuration studied, an average 14% increase in array performance over approximately a 50° range of wind direction was observed. Additionally, three-dimensional vortex interactions behind pairs of VAWT were observed that can replenish momentum in the wake by advection rather than turbulent diffusion. These effects and their implications for wind-farm design are discussed.

Analysis of Hydrodynamic Characteristics of Ocean Ship Two-unit Vertical Axis Tidal Current Turbines with Different Arrangements

Ji, R.; Sun, K.; Wang, S.; Li, Y., and Zhang, L., 2018. Analysis of hydrodynamic characteristics of ocean ship two-unit vertical axis tidal current turbines with different arrangements. In: Liu, Z.L. and Mi, C. (eds.), Advances in Sustainable Port and OceanEngineering. Journal of Coastal Research, Special Issue No. 83, pp. 98–108. Coconut Creek (Florida), ISSN0749-0208.In order to study the hydrodynamic performance of the two-unit turbinesin different arrangements, a reasonable turbine layout plan was proposed to improve the power generation efficiency of tidal power stations. In this paper, the transient numerical simulation of a three-blade vertical-axis tidal current turbine is carried out, and the hydrodynamic performance of the turbine units with different arrangement (tandem, parallel, and staggered) is analyzed, and the influence of the mutual interference between the turbine units on the efficiency of the power generation is explored. Taking into account the same characteristics of the profile of the vertical axistidal current turbine blades along the extension, the model is simplified to two-dimensional. Firstly, based on the open source software OpenFOAM, a k-ω SST turbulence model and a PIMPLE algorithm are used for a 2D vertical axis tidal current turbine. A numerical simulation method is proposed and compared with the experimental results to verify the correctness of the numerical simulation method. Then the operation of a single turbine was simulated, and the variation of energy utilization with the tip speed ratio and the force characteristics of the turbine during operation were obtained. Finally, the vertical axis tidal turbine units with different arrangements are analyzed in detail, and the energy efficiency, force characteristics, and wake field of the vertical axis turbine units are compared and analyzed. For tandem tidal turbine units, the flow distance Dx of the two-unit turbines is used as a variable to study the effect of tidal turbine spacing on the hydrodynamic performance of downstream turbines. For parallel tidal turbines, the influence of the horizontal distance Dy and three different rotations on the hydrodynamic performance of tidal turbines is studied. For staggered turbine units, the relative distance Dr and the relative position angle ψ of the turbine are used as variables to study the relationship between the capacity of the turbine and the two parameters.

Experimental validation of analytical wake and downstream turbine performance modelling

Wake effects in wind farms can cause significant power losses. In order to reduce these losses layout and control optimization can be applied. For this purpose, simple and fast prediction tools for the wake flow are needed. In the first part of this work, five analytical wind turbine wake models are compared to small-scale turbine wind tunnel measurements. The measurements are conducted at several downstream distances, varying the ambient turbulence intensity and upstream turbine blade pitch angle. Furthermore, an adjustment of a recently developed wake model is proposed. Subsequently, the adjusted model is found to perform best throughout all test cases. In the second part, the performance of an aligned downstream turbine is modelled based on the predicted wake flow using a Blade Element Momentum method with guaranteed convergence. In order to consider the non-uniform inflow velocity a mean-blade-element-velocity method is developed. Moreover, a blockage effect correction is applied. A comparison to wind tunnel measurement data shows that the wake velocity as well as the combined power of two aligned turbines are fairly well predicted. Additionally, the presented analytical framework of wake and downstream turbine performance modelling proposes several model improvements for state-of-the art wind farm simulation tools.

Validation of the actuator line method for simulating flow through a horizontal axis tidal stream turbine by comparison with measurements

The purpose of the present work is to evaluate the capability of the Actuator Line Method (ALM) to simulate flow through a horizontal axis tidal stream turbine. A numerical model combining the ALM with large eddy simulation technique is developed and applied to compute the flow past a laboratory-scale tidal stream turbine. The flow field is analysed in terms of streamwise mean velocity, turbulence intensity, turbulent kinetic energy and the decay rate of the maximum turbulent kinetic energy behind the turbine. It is found that the ALM performs well in predicting the mean flow and turbulence characteristics behind the turbine. The flow field predicted show a clear transition from an organised vorticity region near the turbine to a highly turbulent flow downstream. The location of this transition and the controlling parameters are discussed but further investigation, both numerical and experimental is required in order to clarify its effects on the flow structure and the performance of downstream turbines in tidal turbine arrays.

Blind test comparison of the performance and wake flow between two in-line wind turbines exposed to different turbulent inflow conditions

Abstract. This is a summary of the results of the fourth blind test workshop that was held in Trondheim in October 2015. Herein, computational predictions on the performance of two in-line model wind turbines as well as the mean and turbulent wake flow are compared to experimental data measured at the wind tunnel of the Norwegian University of Science and Technology (NTNU). A detailed description of the model geometry, the wind tunnel boundary conditions and the test case specifications was published before the workshop. Expert groups within computational fluid dynamics (CFD) were invited to submit predictions on wind turbine performance and wake flow without knowing the experimental results at the outset. The focus of this blind test comparison is to examine the model turbines' performance and wake development with nine rotor diameters downstream at three different turbulent inflow conditions. Aside from a spatially uniform inflow field of very low-turbulence intensity (TI = 0.23 %) and high-turbulence intensity (TI = 10.0 %), the turbines are exposed to a grid-generated highly turbulent shear flow (TI = 10.1 %).Five different research groups contributed their predictions using a variety of simulation models, ranging from fully resolved Reynolds-averaged Navier–Stokes (RANS) models to large eddy simulations (LESs). For the three inlet conditions, the power and the thrust force of the upstream turbine is predicted fairly well by most models, while the predictions of the downstream turbine's performance show a significantly higher scatter. Comparing the mean velocity profiles in the wake, most models approximate the mean velocity deficit level sufficiently well. However, larger variations between the models for higher downstream positions are observed. Prediction of the turbulence kinetic energy in the wake is observed to be very challenging. Both the LES model and the IDDES (improved delayed detached eddy simulation) model, however, consistently manage to provide fairly accurate predictions of the wake turbulence.

A novel wake energy reuse method to optimize the layout for Savonius-type vertical axis wind turbines

The long wake of a wind turbine has a significant impact on the performance of downstream turbines. Under the inspiration of migrating geese flying in a V or I formation to save energy, a novel wake energy reuse method is proposed to optimize the layout for Savonius-type vertical axis wind turbines (S-VAWT). VAWT wakes include a series of high speed and energy zones. On both sides of the upstream turbine, 7×16 transient two-dimensional numerical simulations are performed with Fluent to investigate wake structure, interaction effect and power coefficients (Cp) of downstream turbines. Based on Kriging Method, a response surface model (Surrogate model) is created to describe the relationship between the optimization objective Cp and layout positions. Finally, particle swarm optimization algorithm is applied to find the optimal relative layout position (5.25 m, −2.18 m) of the downstream turbine. The optimal position is located in the periodic high speed zone of the wake on the advancing blade side. And the optimal position is suitable for multi-turbines in a large wind farm. The optimization results show that Cp of downstream turbines at optimal layout position is significantly increased from 0.2477 to 0.3044 (22.89% higher).

Effect of Upstream Turbine Tip Speed Variations on Downstream Turbine Performance

A wake study and combined power output analysis of an array of two model wind turbines is presented. In a wind farm arrangement wakes behind the upstream turbines directly affect the performance and structural loads of the downstream turbines. In this analysis the characteristics of the mean and turbulent wake flow behind an upstream model turbine is directly related to the performance characteristics of a downstream rotor located at three different downstream locations. First the influence of the upstream turbine's tip speed ratio variation from design conditions on the wake flow and the downstream turbine performance is analyzed. Thereafter, also the turbulence intensity level at the wind tunnel inlet is varied from low (laboratory conditions, TI=0.23%) to high (atmospheric conditions, TI=10.0%). Finally, the combined power output of the two turbine array is evaluated for a matrix of the different scenarios.A significant influence of the background turbulence level on the wake recovery is observed, especially for the intermediate separation distance of x/D=5. Controlling the upstream turbine's tip speed ratio away from its design point does not result in a significant increase in combined power output. Only for the case of low turbine separation distance (x/D=3) and low background turbulence the added kinetic energy in the wake can be recovered by the downstream turbine. For higher turbine separation distances and higher background turbulence, the added kinetic energy diffuses into the freestream flow and cannot be recovered anymore. In average, the combined efficiency is observed to increase by about 2.5% with every additional rotor diameter of turbine separation distance. Thus, this analysis suggests an accurate management of the upstream turbine tip speed ratio in dependence of background turbulence and turbine separation distance when optimizing the power output of a wind farm.

Analyzing complex wake-terrain interactions and its implications on wind-farm performance.

Rotating wind turbine blades generate complex wakes involving vortices (helical tip-vortex, root-vortex etc.).These wakes are regions of high velocity deficits and high turbulence intensities and they tend to degrade the performance of down-stream turbines. Hence, a conservative inter-turbine distance of up-to 10 times turbine diameter (10D) is sometimes used in wind-farm layout (particularly in cases of flat terrain). This ensures that wake-effects will not reduce the overall wind-farm performance, but this leads to larger land footprint for establishing a wind-farm. In-case of complex-terrain, within a short distance (say 10D) itself, the nearby terrain can rise in altitude and be high enough to influence the wake dynamics. This wake-terrain interaction can happen either (a) indirectly, through an interaction of wake (both near tip vortex and far wake large-scale vortex) with terrain induced turbulence (especially, smaller eddies generated by small ridges within the terrain) or (b) directly, by obstructing the wake-region partially or fully in its flow-path. Hence, enhanced understanding of wake- development due to wake-terrain interaction will help in wind farm design. To this end the current study involves: (1) understanding the numerics for successful simulation of vortices, (2) understanding fundamental vortex-terrain interaction mechanism through studies devoted to interaction of a single vortex with different terrains, (3) relating influence of vortex-terrain interactions to performance of a wind-farm by studying a multi-turbine wind-farm layout under different terrains. The results on interaction of terrain and vortex has shown a much faster decay of vortex for complex terrain compared to a flatter-terrain. The potential reasons identified explaining the observation are (a) formation of secondary vortices in flow and its interaction with the primary vortex and (b) enhanced vorticity diffusion due to increased terrain-induced turbulence. The implications of this vortex-terrain interactions on wind-farm performance is observed by comparing two LES simulations of a multi-turbine wind-farm layout (in real actual complex terrain and a made-up flat terrain scenario) with the observed annual power data at the actual wind-farm. The comparison reveals drop in power production due to terrain and wake effects for flatter terrain case. The insights from this study can serve as a step towards enhancing wake-dissipation through either artificial obstruction or artificial terrain modifications.

Incorporating Atmospheric Stability Effects into the FLORIS Engineering Model of Wakes in Wind Farms

Atmospheric stability conditions have an effect on wind turbine wakes. This is an important factor in wind farms in which the wake properties affect the performance of downstream turbines. In the stable atmosphere, wind direction shear has a lateral skewing effect on the wakes. In this paper, we describe changes to the FLOw Redirection and Induction in Steady-state (FLORIS) wake engineering model to incorporate and parameterize this effect.

Investigation of the performance of a staggered configuration of tidal turbines using CFD

This paper investigates the influence of wake interaction and blockage on the performance of individual turbines in a staggered configuration in a tidal stream farm using the CFD based Immersed Body Force turbine modelling method. The inflow condition to each turbine is unknown in advance making it difficult to apply the correct loading to individual devices. In such cases, it is necessary to establish an appropriate range of operating points by varying the loading or body forces in order to understand the influence of wake interaction and blockage on the performance of the individual devices. The performance of the downstream turbines was heavily affected by the wake interaction from the upstream turbines, though there were accelerated regions within the farm which could be potentially used to increase the overall power extraction from the farm. Laterally closely packed turbines can improve the performance of those turbines due to the blockage effect, but this could also affect the performance of downstream turbines. Thus balancing both the effect of blockage and wake interaction continues to be a huge challenge for optimising the performance of devices in a tidal stream farm.