Stream Turbine Research Articles

Experimental and numerical investigations on the performance and wake characteristics of a tidal turbine under yaw

This paper presents an extensive examination of the wake characteristics and hydrodynamic performance of a 1:60 scale horizontal axis tidal stream turbine under yawed inflow conditions. Experimental investigations were conducted in a laboratory flume, while numerical simulations utilized the actuator line method and large-eddy simulation technique. The turbine was subjected to an inflow turbulence intensity of 6% and was tested at five different yaw angles (5°, 10°, 15°, 20°, and 30°). The findings demonstrate a substantial reduction in the power coefficient as the yaw angle increases, with a notable drop of 47.1% recorded at a yaw angle of 30°. Furthermore, numerical simulations of wake characteristics, including mean velocity and turbulence intensity, were examined and compared with measurements, yielding satisfactory agreement. The yawed wake flow exhibited asymmetrical distributions of mean velocity and deviations from the centerline. Additionally, distinct deformations of the yawed wake in the y-z cross sections were observed, indicating a discernible curled kidney shape that intensified with larger yaw angles. Moreover, interactions between the turbine wake and support structures affected the width and turbulence intensity of the near wake, introducing additional unsteadiness that accelerated wake recovery.

Tidal energy extraction modifies tidal asymmetry and transport in a shallow, well-mixed estuary

Tidal energy extraction is increasingly being studied as a potential renewable energy resource in estuaries worldwide. Although it is understood that energy extraction via tidal stream turbines can modify currents and transport within estuaries, it is not clear how the underlying nonlinear physical mechanisms dictating tidal hydrodynamics are modulated. This research investigates the influence of a hypothetical tidal stream turbine array on barotropic tidal processes in a shallow, well-mixed system: the Piscataqua River – Great Bay (PRGB) estuary, using a numerical model. The modeled turbine farm includes 180 turbines which would extract an estimated 44.7 GWh of energy, annually. The tidal hydrodynamic model for the existing condition is validated with in-situ observations of currents and water level before analyzing tidal asymmetry and transport with and without tidal turbines. Results indicate that the tidal turbine array will decrease tidal elevation and current magnitudes system-wide, but generally reduce ebb currents and transport more than flood over most of the estuary footprint, thereby diminishing tidal asymmetry. The smaller asymmetric distortion compared to the no-turbine case is attributed to reductions in the storage volume of water over the estuary’s extensive tidal flat regions between low and high waters which decreases the associated nonlinear intertidal storage mechanism up to 25%. This leads to weakened ebb dominance over estuary sections from the mouth to mid-reaches, where depths are deep enough to keep the combined nonlinear shallow water and frictional effects from asserting control over the storage mechanism. Even in upstream shallow regions where depth-dependent friction controls asymmetry in both cases, the frictional mechanism is reduced only by 10% with turbines. Some environmental considerations of this work are discussed, with focus on sediment transport, water quality, and ecology.

The impact of yaw motion on the wake interaction of adjacent floating tidal stream turbines under free surface condition

Several works put emphasis on the maturation of floating tidal stream turbine systems, deemed viable for sites at deep water depths. The objective of this research is to determine, through a CFD model, the yaw effect on the wake and functioning of a floating twin-turbine system under wave-induced motion. The simulation certainty is corroborated against experiments on a 1:7 piled twin-turbine system (Froude similarity). Collectively, the variation and deficiency of the power and thrust coefficients are amplified with the yaw frequency and amplitude. Whereas the individual wakes collide, depending on the yaw feature and turbine cross-current spacing, resembling a smoke-plume-type pattern. The larger cross-current spacing shortens the wakes and reduces near-wake deficit at mid-row due to the greater energy exchange from the ambient flow. Regardless of the yaw feature, the transversal wake deficits turn from double (majority symmetrical) at near wake into triple distributions thenceforth, before flattening at far wake. Importantly, the wake unsteadiness and recovery rate are more obvious with period, as opposed to amplitude effect. As yaw operation is imminent, contributed by flow skewness and platform yaw motion, it will be constructive to implement natural frequency analysis to prevent vortex-induced vibrations and mechanical weariness in the floating system.

Quantifying the surge-induced response of a floating tidal stream turbine under wave-current flows

Understanding the impact of dynamic effects induced by wave-current conditions on the hydrodynamic performance of a floating horizontal axis tidal turbine (HATT) is crucial toward developing floating tidal turbines to harness tidal energy in deep water sites. The complicated of the wake of a HATT has not yet been fully understood. In this paper, a Computational Fluid Dynamics (CFD) model used to study the performance of a turbine supported by a moored floating platform, due to surge only and in wave-current flows. The CFD model is compared against piled turbine tests, providing an error of 1.36% in power coefficients at the studied TSR = 3.9. It was shown that surge motion caused by even a small wave height or wavelength has a significant effect on the thrust and torque of the rotor. The wave height and period have a remarkable effect on the fluctuation of the hydrodynamic performance due to the induced rotor velocity. The surge motion affects the wake velocity recovery and vortex structure development. For a fuller understanding, future work could explore the negative effects such as induced blade fatigue and platform instability arising from surge motion, as to design cost-efficient turbines, supports and arrangements.

High-fidelity modelling of a six-turbine tidal array in the Shetlands

Micro-siting tidal stream turbines in a confined seabed area requires a extensive understanding of the flow dynamics over the water column at turbine deployment locations so that operating conditions are assessed, wake effects can be estimated to infer the energy yield [1], or bathymetry effects can be quantified. Tidal currents have the advantage of being highly predictable and mostly bidirectional but the uneven bathymetry found at most of sites introduces a high variability to the flow conditions within relatively short distances. Considering future tidal turbine arrays will comprise dozens of devices, deploying ADCPs at each turbine position would be very expensive or very time consuming, outlining the need for accurate modelling tools to be used as digital twins in micro-siting. Shallow-water models are widely adopted in preliminary design of tidal arrays but fail to capture the three dimensional nature of the flow and predict deflected wakes whose streamwise length is also over-predicted [2]. Thus, eddy-resolving method are required to fully capture the turbulence from the free-stream flow, induced by turbines and from bathymetry. \\
 This study provides a real-project application of the state-of-the-art large-eddy simulation (LES) code DOFAS (Digital Offshore Farms Simulator) [3] to the six 100kW-turbine array deployed by NOVA Innovation Ltd. in the Shetlands, UK [4]. The bathymetry data has been obtained from EMODnet database with the velocity profiles set at the inlet condition of both ebb and flood tides imported from Macleod et al. (2019) [4]. The deployment site is characterised by steep slopes with a maximum depth of 45 m at the cross-section where turbines are located. The bathymetry has a downwards slope when the flow goes in the ebb tide direction whilst upstream during flood tide. The tidal rose indicated a slight deviation of about 20$^{\circ}$ between ebb and flood directions. The turbines have a diameter ($D$) of 9 m attached to a 10 m long hub whose diameter is 1 m. Three array configurations have been studied: (i) single row of three turbines, (ii) two rows of turbines spaced 8$D$, and (iii) two rows of turbines spaced 12$D$. The computational domain extends over 600 m by 300 m in the horizontal plane yielding 540 million cells, requiring 32,500 CPU hours to compute 30 min of physical time.\\
 Results show that bathymetry effects at this site play a larger role when designing the location of the secondary row of turbines compared to wake effects from upstream turbines. During the ebb tide, the increase in water depth reduces the wake recovery far downstream so that the array with 12$D$ row spacing has a lower performance than the 8$D$ one with approx. 30\% decrease in energy yield. Conversely, the uphill shape of the bathymetry during the flood enables a fast wake recovery so that the downstream row experiences almost no energy yield loss due to wakes.

Large-eddy simulations of interaction between surface waves and a tidal turbine wake in a turbulent channel

Tidal stream turbines are now being developed for array deployments, largely at sites with relatively shallow water depths on either bed-supported, or floating support structures. Proximity to the free-surface presents design challenges with increased exposure to wave-induced kinematics leading to potential for increased peak- and fatigue-loads. Free surface proximity can also alter wake recovery rates which can influence the siting, and operation, of further turbines. To-date the impact of waves on turbine loading and on wake recovery has receivedlimited attention, generally for specific combinations of conditions reproducible in experimen tal facilities [1-2] or numerical models [3]. Improved understanding of how waves affect both turbine loading, and wake dynamics is necessary to inform the development of appropriate load prediction and mitigation methods and to further parameterise wake recovery to inform array siting.
 This work presents CFD analysis of the loading and wake of a three-bladed horizontal axis tidal turbine within a wide, shallow channel with a turbulent inflow developed using a synthetic eddy method and free surface waves modelled using a Level-Set Method (LSM). The turbine and wave conditions considered are based on prior experimental studies [1] within a channel depth h = 0.45 m and mean flow U = 0.47 m/s. The simulated channel is width 3.67h and length 88h and long-crested regular waves are imposed, with the focus of this study on waves with non-dimensional wavenumber kh = 2.8, comparable with experimental conditions. Simulations are accomplished using the in-house large-eddy simulation (LES) code DOFAS(Digital Offshore Farms Simulator) [4], which adopts an Actuator Line Method (ALM) to resolve the turbine blades. LSM is used to model the air-water interface in an accurate manner [5] with waves can be generated in DOFAS using linear or second-order Stokes theories with an absorption layer placed at the outlet of the domain to avoid wave reflections. At the inlet a mean logarithmic velocity profile is imposed over which artificial turbulence is added. Simulations were run for 400 s of physical time on 8,000 cores using ARCHER2.
 The waves studied are shown to alter the rate of wake recovery, increasing the rate in the near-wake of the turbine and slightly reducing the rate beyond eight diameters downstream. Analysis of turbulence characteristics indicates a significant variation across the water column due to wave action. Propagation over the turbine wake also introduces directionality to the wave field, which is associated with the change of wave-speed over the wake region. Modal decomposition analysis of the velocity fluctuations with Proper Orthogonal Decomposition(POD) reveals that the wake dynamics behind the turbine change due to the waves.

Laboratory Tests Assessment of a Mechanical Sensor-less MPPT Control Strategy for Tidal Turbines

The purpose of this study is to demonstrate through towing tank experiments the effectiveness of a novel sensor-less Maximum Power Point Tracking (MPPT) control for Tidal Stream Turbines (TST) under fluctuations of the onset flow. Ocean energies will play a crucial role in the renewable energy sector over the next decades. Instream turbines for tidal currents are a rapidly maturing technology to exploit a highly predictable energy source. However, short-term fluctuations on the inflow velocity caused by waves or turbulence determine fatigue loads that affect system reliability. Power control strategies to maximize the energy yield can be also used to mitigate the effects of transient loading on drivetrain components. Aim of this paper is to present a straightforward and robust MPPT control method based on the linear relationship between the current and voltage squared of the generator's DC outputs. The method requires pre-determined turbine characteristics to establish the control reference that is effective across operating conditions. The proposed MPPT model was derived mathematically through linearization and simplifications of the turbine power conversion system and validated by model tests carried out in the wave-towing tank facility of CNR-INM in Rome, Italy, using the 1.5 m diameter Tidal Turbine Testing (TTT) device developed at the Queen’s University Belfast (QUB). In the study, a conventional TSR control method was also considered in order to perform a comparative analysis of system response to inflow speed fluctuations with time scales comparable to turbine revolution periods. TSR control was tested using two control references: TSR = 5 (design point) and TSR = 6 (over-speed zone) to verify the operation of the turbine under different loading conditions. The tests were conducted in two scenarios: calm water (steady state) and unsteady inflow with a regular (sinusoidal or monochromatic) waveform, with amplitude chosen to simulate an extreme wave case. The power output was measured from the turbine during regular wave conditions and compared to results from steady flow to assess the impact of wave-induced velocity on turbine performance (Fig. 1). Test results showed that by using the proposed MPPT control strategy, the algorithms converged to the maximum power coefficient (Fig. 2), which validates the proposed methodology. Results also demonstrated the capability of the proposed MPPT to significantly reduce mechanical loads fluctuations as compared to the TSR control. In the full-length paper, the proposed MPPT control strategy is outlined, the test methodology, set-up and conditions are described, and main results are presented and discussed.

Investigating the impact of multi-rotor structure shadowing on tidal stream turbine performance

As the tidal stream energy sector develops, reducing the Levelised Cost of Energy (LCOE) is essential to sustain commercialisation. Modular multi-rotor foundations, with bi-directional turbines, reduce offshore operational complexity through smaller turbine diameters and lift weight, in turn reducing the device Operational Expenditure (OpEx). With the introduction of modular, multi-rotor foundations, the wake-induced impacts that these structures have on turbine performance must be investigated to better estimate energy yield, loading, and fatigue life. This study sets the scene for investigating the relationship between the turbulent wake generated by a modular ballast weighted foundation and 2-bladed Horizontal Axis Tidal Turbine (HATT) motivated by the HydroWing multi-rotor device concept. The presented work aims to determine the broader magnitude and severity of the loads and establish a robust methodology to be followed with further high-fidelity modelling. Initially, a transient RANS Computational Fluid Dynamics (CFD) simulations environment with a sliding mesh is configured and validated against experimental data. A turbine in free-stream isolation is simulated as a benchmark case with the modular foundation sequentially introduced to analyse the impact of the structure. Key findings suggest that operating turbines downstream of the multi-rotor foundation could cause a 20% fluctuation in thrust loading at a 1.82 Hz frequency resulting in a mean Cp reduction of 8% over a revolution.

Automated detection of wildlife in proximity to marine renewable energy infrastructure using machine learning of underwater imagery

Environmental interactions of marine renewable energy (MRE) projects are challenging to monitor, and key questions remain about their potential impacts. Processing large volumes of environmental data acquired from submarine monitoring and the use of machine learning to identify presence and interactions of marine wildlife with MRE infrastructure are powerful tools for assessing the environmental response to MRE infrastructure. The use of automated image analysis for species identification and enumeration using algorithms like convolutional neural networks can vastly reduce the time required to extract usable data from submarine imagery compared to manual expert processing. We present a novel industry-ready image processing workflow for automated wildlife detection developed using 1000+ hours of underwater video footage obtained by Nova Innovation Ltd. from their operational tidal stream turbine array at Bluemull Sound in Shetland, Scotland. The objective of this work was to develop a workflow and associated algorithms to automatically filter many hours of underwater video, remove unwanted footage, and extract only video containing marine mammals, diving birds or fish. The workflow includes object detection through advanced image analysis, image classification using machine learning, statistical analyses such as quantification of data storage reduction and number of detections, and automated production of a summary report. Blind tests were undertaken on a subset of videos to quantify and iteratively improve the accuracy of the results. The final iteration of the workflow delivered an accuracy of 80% for the identification of marine mammals, diving birds and fish when a three-category (wildlife, algae, and background) classification system was used. The accuracy rose to 95% when a two-category system was used, and objects were classified simply as ‘target’ or ‘non-target’. The entire workflow can be run from video inception to production of an automated results report in approximately 30 minutes, dependent on size of input data, when environmental conditions such as water clarity and key species of interest are familiar to the algorithm. The accuracy and runtime speed of the workflow can be improved through expanding the training dataset of images used in the development of this initial tool by including additional species and water conditions. Application of this workflow significantly reduces manual processing and interpretation time, which can be a significant burden on project developers. Automated processing provides a subset for more focused manual scrutiny and analysis, while reducing the overall size of dataset requiring storage. Auto-reporting can be used to provide outputs for marine regulators to meet monitoring reporting conditions of project licences. Integration of this workflow with automated passive acoustic monitoring systems can provide a holistic environmental monitoring approach using both underwater imagery and acoustics.

Characterisation of turbulent flow and the wake of a tidal stream turbine in proximity to a ridge

Fast tidal currents are generally found in shallow water depths where tidal turbines can be deployed to operate. In complex environments in which there is an irregular bathymetry, seabed shape changes can induce pressure gradients that accelerate or decelerate the flow depending on the slope and relative depth, affecting turbine wake recovery. In this study, a laboratory scale turbine, represented numerically using an Actuator Line Method (ALM), is computed using Large-Eddy Simulations (LES) over a flat-bed and in presence of three short ridges with varying streamwise lengths. Turbines are positioned at several locations, namely at ridge-centre (0D) and at 2D upstream and downstream from the foot of the ridge to establish the influence of location on wake recovery rate. Turbine operating point is selected to yield a constant tip-speed ratio based on the disc-averaged velocity at each location obtained from a precursor simulation run without turbines. Results show that, relative to the same turbine in a flat channel, there is a noticeable enhancement of the rate of wake recovery when turbine is sited upstream of the ridge and it experiences high fatigue loads when sited downstream of the ridge. Implications for array design regarding performance losses due to turbine- and bathymetry-induced wakes are drawn.

An adaptive yaw method of horizontal-axis tidal stream turbines for bidirectional energy capture

Tracking the flow direction is one of the effective ways to harvest more energy for a horizontal-axis tidal stream turbine (HATST). This paper presents a novel HATST design that incorporates a yaw method with a tail wing, inspired by horizontal-axis wind turbines. The design enables the HATST to adaptively yaw toward the bidirectional flow with a reciprocating rotation. To ensure stability, a small yaw angle was reserved and permanent magnets were employed to hold the yaw mechanism steady. The kinetic equations of the yaw mechanism were established, and the influence of the yaw shaft's position and the tail wing's mass on the yaw performance was analyzed. A test model was constructed to validate the design and analysis, and the optimum parameters were discussed. Experimental results demonstrated that the HATST yawed well toward the inflow and maintained the designed yaw angle of approximately 5° at different velocities. Compared with the device without magnetic-assisted yaw, the HATST achieves more than 4.47% increase in output power in the velocity range of 0.15 m/s to 0.31 m/s, and exhibits minimal swing amplitude. This research provides a novel and practical solution for the effective utilization of bidirectional tidal steam energy.

Validation of Actuator Line Modeling and Large Eddy Simulations of Kite-Borne Tidal Stream Turbines against ADCP Observations

The representation of tidal energy in future renewable energy systems is growing. Most of the current tidal turbine designs are limited by the minimum current velocity required for efficient operation. The Deep Green (DG) is a kite-borne tidal power plant designed to sustain efficient operation in tidal current velocities as low as 1.2 ms−1. This could increase the geographical areas suitable for large-scale tidal power arrays. Numerical modeling of the Deep Green was carried out in a previous study using large eddy simulations and the actuator line method. This numerical model is compared with acoustic Doppler current profiler (ADCP) measurements taken in the wake of a DG operating in a tidal flow under similar conditions. To be comparable, and since the ADCP measures current velocities using averages of beam components, the numerical model data were resampled using a virtual ADCP in the domain. The sensitivity of the wake observations to ADCP parameters such as pulse length, bin length, and orientation of the beams is studied using this virtual ADCP. After resampling with this virtual ADCP, the numerical model showed good agreement with the observations. Overall, the LES/ALM model predicted the flow features well compared to the observations, although the turbulence levels were underpredicted for an undisturbed tidal flow and overestimated in the DG wake 70 m downstream. The velocity deficit in the DG wake was weaker in the observations compared to the LES. The ALM/LES modeling of kite-borne tidal stream turbines is suitable for further studies of array optimization and wake propagation, etc.

Study on the dynamics and wake characteristics of a floating tidal stream turbine with pitch motion under free surface

To improve knowledge of the unsteady hydrodynamic characteristics of a floating horizontal-axis tidal turbine (HATT) in complex marine environments, a computational fluid dynamics (CFD) numerical method is established to analyze the functioning of a HATT under free surface and pitch conditions: an amplitude of 2.5°–12.5° and a period of 3–15 s. The appropriateness of the CFD method is validated against piled turbine tests in a circulating flume, which turned out to be only 1.43% off at the rated tip speed ratio. The power and thrust coefficients exhibit periodic variation with a frequency twice the pitch's motion. From the ecological perspective, the wake velocity field presents radial warps accompanied by several ellipsoidal low-velocity core regions, which corresponds to the fused vortex rings in the vortex zone. Notably, the wake is more influenced with large rather than small amplitudes and periods; meanwhile, the wake is more sensitive to frequency changes than to amplitude changes. The results could lay a foundation for future research into more complex motion response of floating tidal turbines.

Assessment of turbulence correction for actuator-line model of a horizontal-axis tidal stream turbine in near-wake region

Near-wake characteristics of a turbine play an important role in turbine–wake interactions and performance assessment in turbine arrays. In this study, the near-wake flow behind a laboratory-scale tidal stream turbine is simulated and compared with experimental data. An actuator-line model is used to represent the rotating blades. Further, two physics-based turbulence corrections are proposed for unsteady Reynolds-averaged Navier–Stokes (URANS) modeling of the tidal stream turbine. These corrections seek to model additional turbulent production near the blade boundary layer and in the tip shear region. The data analysis for the fluctuating velocity spectrum in the experiment highlights that the turbulence kinetic energy (TKE) can be decomposed into three parts: the background turbulence from the onset flow, rotor-scale turbulence, and blade-induced turbulence. The blade-induced turbulence dominates near the rotor plane and decreases sharply beyond one diameter downstream. Near-wake profiles of velocity and TKE are compared with experimental data. The results show that turbulence corrections in the URANS model enhance the production of turbulence induced by the blade rotation. It can improve turbulence prediction in the near-wake region with a minor impact on the loads and wake velocity.

Numerical investigation of the local impact of hydrokinetic turbine on sediment transport—Comparison between two actuator models

Hydrokinetic turbines interact with the dynamics of the sedimentary bottom at small and large scale. Despite the interest that the study of these interactions deserves, little research has been published in the field. In this paper, we investigate by numerical simulation the interaction between modeled hydrokinetic turbines and bed load under clear-water scour conditions. The mixture of water and sediment is accounted for by an Eulerian multiphase model developed in the open source platform OpenFOAM. The turbine blades are parameterized by two models: the Blade Element Method (BEM) and the Actuator Disc Theory (AD). A good agreement with measurements is obtained in the near wake. The effects of the two different turbine models on the bedload sediment transport and on the wake characteristics are then examined. The local impact of the turbine modeled by BEM is more pronounced on the bed than the one modeled by the AD. So, the BEM modeling is preferable to the AD one for local studies of the impact of a turbine on the bed morphology. However, combining BEM with the two-phase fluid-sediment is time consuming and make difficult the use of this method to study a farm of several stream turbines. In such a case the use of AD is still remains recommended for now. Moreover, more studies must be done at real scale as the turbine rotational speed is relatively low and could induced less impact of the swirl on the bottom shear stress.

Effects of surge and roll motion on a floating tidal turbine using the actuator-line method

This paper employs a dynamic and sliding mesh in the simulation of both uncoupled and coupled surge and roll motions of a tidal stream turbine, utilizing a modified actuator-line method. The modification involves the relocation of blade elements in relation to the grid. Detailed analyses are conducted on the Cp and Cz variations in surge, roll, and coupled motions at various frequencies and amplitudes. It is observed that changing the amplitude and frequency of surge and roll motions both impacts the amplitude of Cp and Cz. Interestingly, the Cp and Cz variations in surge motion are inversely proportional to velocity variations, while they are directly proportional in roll motion. The influence of the surge motion on Cp Cz plays a major role, while the addition of the roll motion increases the mean values of Cp and Cz. Due to the combination of the wake characteristics of both surge and roll, the coupled motion wake exhibits a contraction–expansion oscillation pattern. In a coupled motion with equal periods, the ring and strip tail vortex characteristics of both motions are apparent. A surge period increment diminishes the surge's tail vortex characteristic, whereas an increase in the roll period gradually erodes the roll's tail vortex characteristic. The coefficient variation of the tangential and normal forces (cn, ct) in combined motion mirror that of surge motion, presenting a convex table per surge cycle with depressions at the 1/2T and 1T points. The peak of cn and ct in surge motion are approximately 0.28 and 0.03, respectively, while in roll motion, they are around 0.261 and 0.025. The exploration of cyclic stress impacts on the turbine, and the potential instability on the platform could be valuable directions for future research.

Experimental investigation of wake and thrust characteristics of a small-scale tidal stream turbine array

Tidal stream turbines (TSTs) are usually organized into an array to extract energy from tidal stream efficiently. A deep understanding of wake structures and thrust characteristics of tidal stream turbine array (TSTA) can contribute to its layout optimization. The wake and thrust characteristics of two arrangement types of TSTAs were experimentally investigated and compared. Influences of the spacing distance between turbines were accordingly analyzed and discussed. Through comparison of velocity distribution between two TSTAs, it was found that the wake deficit area of the turbine array significantly increased with an additional upstream turbine. A larger distance was in need for the downstream turbine to recover its wake velocity to free velocity magnitude. Adding a turbine upstream, reduces the flow velocity difference between the downstream turbines, resulting in a better wake merge. The spacing change between arrays is directly related to the position and range of the array wake merge. Moreover, reducing the lateral spacing could potentially facilitate quicker wake merging, while increasing the longitudinal spacing may result in the wake merge area shifting upstream. Additionally, the mono-pile support structure was found to significantly decrease velocity magnitude and increase turbulence intensity, particularly in the near wake region.

Experimental investigation of the seabed topography effects on tidal stream turbine behavior and wake characteristics

Physical modelling was performed to study the hydrodynamics and wake interferences of a tidal stream turbine sited in close proximity to different seabed elements. The seabed topography variation had a significant effect on the tidal stream turbine behavior. The average power output of the turbine with the presence of the small seabed topography increased by about 11%, while the power output of the turbine sited in close proximity to the larger seabed topography was reduced by approximately 40% compared to that with a flat bed. Additionally, detailed flow field measurements of the turbine wake revealed the seabed topography variation effects on the wake characteristics. The small seabed topography increased the average turbulence intensity in the near wake region behind the turbine and made the flow velocity recovery slightly faster than the case with flat bed. In contrast to the small seabed topography, the larger topography had a certain inhibitory effect on wake recovery. The results presented in the current study not only offer a validation database for wake models but can also be used to optimize the site selection and rotor placement of tidal turbines for a higher power yield.

Research on Wake Field Characteristics and Support Structure Interference of Horizontal Axis Tidal Stream Turbine

The harnessing and utilization of tidal current energy have emerged as prominent topics in scientific inquiry, due to their vast untapped resource potential, leading to numerous investigations into the efficacy of hydrokinetic turbines under various operational conditions. This paper delineates the wake field characteristics and performance of horizontal axis tidal stream turbines under the influence of support structures, using a comprehensively blade-resolved computational fluid dynamics (CFDs) model that employs Reynolds-averaged Navier–Stokes (RANS) equations in combination with the RNG k-ε turbulence model. To achieve this, the study utilized experimental tank tests and numerical simulations to investigate the distribution characteristics and recuperative principles of the turbine’s wake field. The velocity distribution and energy augmentation coefficient of the wake field showed strong agreement with the experimental results. To further assess the effect of support structures on the flow field downstream of the unit and its performance, the hydrodynamic attributes of the turbine wake field were analyzed with and without support structures. The interference elicited by the support structure modified the velocity distribution of the near-wake flow field, resulting in a 4.41% decrease in the turbine’s power coefficient (Cp), significantly impacting the turbine’s instantaneous performance.

Tidal Stream Turbine Biofouling Detection and Estimation: A Review-Based Roadmap

In the context of harvesting tidal stream energy, which is considered a promising source of renewable energy due to its high energy density, stability, and predictability, this paper proposes a review-based roadmap investigating the use of data-driven techniques, more specifically machine learning-based approaches, to detect and estimate the extent of biofouling in tidal stream turbines. An overview of biofouling and its impact on these turbines will be provided as well as a brief review of current methodologies and techniques for detecting and estimating biofouling. Additionally, recent developments and challenges in the field will be examined, while providing several promising prospects for biofouling detection and estimation in tidal stream turbines.