Horizontal Axis Tidal Turbine Research Articles

A novel generative approach to the parametric design and multi-objective optimization of horizontal axis tidal turbines

As the demand for ocean energy continues to grow, the development of efficient design and optimization methods for tidal current turbines is crucial. Traditional approaches, often based on parameterized models, face challenges in fully capturing the intricate geometric features of turbine blades, limiting the optimization space and affecting convergence efficiency. In response, this study introduces a novel design methodology for horizontal axis tidal turbines (HATTs) using a variational autoencoder generative adversarial network (VAEGAN) model. This approach uses unsupervised learning from a custom dataset to generate new HATT designs, with the VAEGAN model encoding distinct geometric features of turbine blades within a compact latent space, enabling more efficient design space exploration and facilitating the discovery of innovative shapes. Furthermore, in the multi-objective optimization process targeting both hydrodynamic performance and structural strength, the reduced dimensionality of the design variables accelerates convergence while maintaining a broad and meaningful design space. The proposed methodology demonstrates the VAEGAN model's ability to generate diverse and effective turbine blade designs, highlighting its potential as a powerful tool in advancing HATT technology.

Near wake evolution of a tidal stream turbine due to asymmetric sheared turbulent inflow with different integral length scales

Tidal stream turbines deployed at highly energetic open water sites are subjected to sheared inflow in the rotor plane. The inflow shear is expected to cause asymmetric loading on the rotor blades and affect the downstream wake. In the current study, two different turbulent inflow conditions, static-high shear and dynamic shear, were generated via an active-grid turbulence generator. A 1:20 scaled three-bladed horizontal axis tidal turbine model was tested in those conditions. The results were compared to a quasi-laminar case with no imposed turbulence or shear. The results show that the high shear reduces the average performance, with a drop of up to 16% in the optimal power coefficient. Besides, the shear profiles increase torque fluctuations and induce significant differences in wake hydrodynamics between the high-speed (upper) and low-speed (lower) regions. The large integral length scales further enhance the load fluctuations perceived by the rotor but have a negligible effect on the mean wake field quantities. The wake recovery was found to be ∼2 to 4 times faster in the upper half region than in the lower region in the near wake. The lower half region featured a faster breakdown of tip vortex structure and a rapid drop of swirl number, a phenomenon conjectured to be a consequence of the strong turbulence intensities and Reynolds stresses in the lower half region. The sheared turbulent inflow also results in a very intensive energy redistribution process towards large-scale, low-frequency motions, which is important to the downstream turbines.

Multi-Objective Optimization Design of Dynamic Performance of Hydrofoil with Gurney Flap

The horizontal axis tidal turbine, as a crucial device for capturing tidal energy, has gained significant attention because it has better energy efficiency performance. Enhancing the performance of foils, a vital part of tidal turbine blades, can significantly improve tidal turbine performance. Among numerous methods to enhance the foil performance, the Gurney flap has gained significant attention due to its avoidance of complex structural design. Currently, there is limited research on optimizing the design of Gurney flaps while considering the dynamic performance of foils. In this study, the S809 foil with a blade cross-section was selected as the research subject, a multi-objective optimization design platform was created by integrating a multi-objective optimization algorithm with Computational Fluid Dy-namics (CFD) numerical simulation techniques. The objective of this platform is to enhance the dynamic performance of the hydrofoil by optimizing the geometric structure of the Gurney flap. The improvement of dynamic lift and the size of the dynamic stall hysteresis loop are used as objective variables in this study to evaluate the hydrofoil’s dynamic performance. The optimal Latin hypercube design method is used in the optimization process to choose sample locations, and the Kriging approximation model is used to determine the relationship between the design variables and the objective variables. Meanwhile, the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) is used to create a multi-objective optimization platform for solving the optimization problem, and the optimized results are validated using CFD. Comparative validation results show that quantifying the dynamic performance during hydrofoil pitching oscillation and using the optimal Latin hypercube design method and Kriging approximation model for optimizing the Gurney flap structure is rational and accurate. This study explores the mechanism of the Gurney flap through in-depth CFD numerical simulations and finds that the Gurney flap affects the flow characteristics at the hydrofoil’s trailing edge, thereby influencing the performance. It increases the pressure difference between the pressure and suction surfaces, thus enhancing the hydrofoil’s lift. Finally, this article provides three recommended parameters to improve the dynamic performance of the hydrofoil. This research can serve as a reference for the application of Gurney flaps in tidal turbine blade design.

Study on the hydrodynamic and wake characteristics of variable speed control of horizontal axis tidal turbine under surge motion

Study on the hydrodynamic and wake characteristics of variable speed control of horizontal axis tidal turbine under surge motion

Blockage and submersion depth effects on horizontal-axis tidal turbine (HATT) in a shear flow environment with wave–current interaction

Blockage and submersion depth effects on horizontal-axis tidal turbine (HATT) in a shear flow environment with wave–current interaction

Orca hydrofoil shape optimization using Bezier curve and artificial neural network – Multiple objective genetic algorithm for low flow velocity

Tidal energy is a clean and predictable power source commonly harnessed using horizontal-axis tidal turbines. The power generation process of these turbines is influenced by various elements, including the hydrofoil performance metrics such as the lift coefficient, drag coefficient, and lift-to-drag ratio. This study introduces the utilization of the Orcinus Orca hydrofoil for horizontal-axis tidal turbines. The Orcinus Orca geometry was obtained by modifying the NACA0021 airfoil. Subsequently, Bézier curve parameterization was employed to achieve a smooth hydrofoil profile. The study further deployed an artificial neural network coupled with a multi-objective genetic algorithm, targeting hydrofoil shape optimization at a low flow velocity of 0.5 m/s. The aim of this optimization was to augment the lift coefficient and decrease the drag coefficient, thereby amplifying the lift-to-drag ratio. The findings reveal a significant enhancement in performance, as the optimized Orcinus Orca hydrofoil exhibits a remarkable increase of 42.78 % and 27.93 % compared to the original Orcinus Orca and the Bézier-modified Orcinus Orca hydrofoils, respectively.

Tidal turbine hydrofoil design and optimization based on deep learning

The optimal design of hydrofoils is critical to improve the hydrodynamic performance of the tidal turbine. However, the global optimization of hydrofoils is limited by the high dimensionality of the design space, which requires extensive computational fluid dynamics simulations. This paper proposes an interactive framework for hydrofoil design and optimization based on deep learning. Generative adversarial networks are used to parameterize the hydrofoil design, which automatically learns representations from existing hydrofoils and controls new hydrofoil generation using fewer variables to reduce optimization dimensions. Moreover, the surrogate model based on convolutional neural networks is constructed, which realizes the mapping of hydrofoil design and operating parameters to hydrodynamic performance parameters. The framework can generate a large number of smooth and realistic hydrofoils with three design variables and quickly predict the performance, enabling effective optimization design of hydrofoils. The results show that the optimized hydrofoil shapes have larger lift-to-drag ratios than those of the common hydrofoils. Furthermore, the optimized hydrofoil is applied to the design of 3D horizontal axis tidal turbine blades. The simulation results show that the framework is effective and stable, which can facilitate the design of tidal turbine rotors and provide hydrofoils with higher power coefficients.

A novel generative–predictive data-driven approach for multi-objective optimization of horizontal axis tidal turbine

Tidal turbines play a critical role in converting the kinetic energy of water into electricity, contributing significantly to energy conversion. However, the current optimization design of these turbines involves computationally intensive simulations, leading to higher design costs. Additionally, traditional parameterized modeling methods, constrained by predefined design parameters, limit the exploration of innovative designs. In response, this study introduces an innovative data-driven “generative–predictive” design approach comprising a generative model and a predictive model. The generative model autonomously learns feature representations from existing turbines and leverages this knowledge to generate a novel set of turbines with superior hydrodynamic performance. Subsequently, an efficient performance evaluation is conducted using a predictive model for the generated turbines. Compared to the current parameterized modeling approaches, the proposed approach is combined with multi-objective optimization algorithm to optimize the tidal turbine hydrodynamic performance. Research results demonstrate that the generative model, trained on gradients, can generate highly complex turbines with minimal latent vectors. Through transfer learning, the predictive model exhibits robustness and accuracy, effectively guiding the design process. In the final optimization comparison, the proposed generative–predictive design approach requires only 4% of the optimization time while achieving results similar to or surpassing traditional design approaches. This approach proves to be a powerful tool for guiding the efficient and optimized design of turbines.

An experimental study of the thrust and power produced by a 1/20th scale tidal turbine utilising blade winglets

Winglets have been employed in the aviation industry to reduce vortices generated at aircraft wings, decreasing drag, and hence increasing fuel economy. For rotating applications previous experimental and numerical studies addressed the application for wind turbines and suggested winglets facing backwards on the suction side of a blade could increase the power capture. This paper presents experimental work using a scale 3-bladed horizontal axis tidal turbine. An oil-based paint flow visualisation coupled to blade thrust and torque measurements helped to identify the mechanism behind the phenomenon affecting the performance of winglets facing the suction side of a turbine blade. The results show that on average a winglet facing downstream decreases the power coefficient 1–2% and increases the thrust coefficient up to 6% for tip speed ratios 5.0–7.0. On the other hand, a symmetrically mirrored winglet facing upstream increased the power coefficient by 1–2%, and the thrust coefficient by 3–4%. Winglets have the potential to provide a meaningful increase to power capture at minimal additional capital cost without increasing rotor diameters. Further work to optimize pressure‐side winglets should be conducted.

Study on the performance of a floating horizontal-axis tidal turbine with pitch motion under wave–current interaction

Waves can induce motion in the floating platforms that support tidal turbines, affecting their hydrodynamic loads. To study the non-constant hydrodynamic of floating tidal turbines in a wave condition, this paper investigates the effect of pitch motion on the power coefficient (CP), thrust coefficient (CT), and wake flow of a tidal turbine using computational fluid dynamics. A pitch motion experiment is designed to verify the validity of the numerical method. The results show that the CP and CT exhibit periodic fluctuations under pitch motion, with the fluctuation period being consistent with the pitch period. Waves do not change the overall fluctuation trend of the CP and CT, but they do complicate the fluctuations and increase the likelihood of blade fatigue damage. Pitch motion reduces the mean power, with large-amplitude pitch motions particularly likely to result in severe power loss. The low-velocity region of the wake under pitch motion exhibits significant periodic oscillations. The wake is more susceptible to the pitch period than the pitch amplitude, and small-period pitch motions force the wake to deform earlier, accelerating wake vortex dissipation and velocity recovery. Increasing the immersion depth reduces the effect of waves on tidal turbine performance, but is not conducive to wake recovery. In summary, the rational design of the immersion depth and limiting the movement amplitude of the floating platform have the potential to prolong the working life of tidal turbines and increase their power output.

Unsteady effects of a winglet on the performance of horizontal-axis tidal turbine

A tip winglet can reduce the induced drag and the load fluctuation of a blade, considerably improving the hydrodynamic performance of a tidal turbine. Up to now, there are fewer studies on the unsteady effects of winglets, which limits the application of this design scheme. In this paper, a tidal turbine model is established based on computational fluid dynamics (CFD) and verified by a flume experiment. Then, unsteady effects on the turbine blade are analyzed considering different winglet lengths and cant angles. According to the study, the blade performance is optimal when the winglet cant angle is 45°, with about 11% efficiency improvement and about 8% increase in axial force; as the winglet length increases, the performance tends to further improve. In addition, this study demonstrates that the reason why a winglet can reduce blade load fluctuations is that the winglet takes the tip vortex generation position away from the blade rotation plane, instead of reducing the tip vortex intensity.

DLFSI: A deep learning static fluid-structure interaction model for hydrodynamic-structural optimization of composite tidal turbine blade

Horizontal axis tidal turbines (HATT) conversion of ocean tidal waves into electricity represents a promising source of clean and sustainable energy. However, the widespread adoption of these turbines has been hindered by persistent challenges, primarily stemming from the high costs associated with their construction and maintenance; and efficient conversion of tidal energy. Addressing these challenges is paramount for propelling tidal turbine technology and ensuring its economic viability. This study focuses on the efficient conversion of tidal energy into electricity by optimization of composite material turbine blades which is a complex problem that spans multiple physical domains, including hydrodynamics (the study of water flow) and structural mechanics (the study of material behavior under loads). To tackle these multifaceted challenges, we introduce an innovative DLFSI (Deep learning fluid-structure interaction) model which represents a groundbreaking approach to predict and optimize the hydrodynamic and structural performance of tidal turbine blades. DLFSI leverages the power of convolutional neural networks (CNN) to recognize intricate geometric features of turbine blades rapidly and accurately. By seamlessly integrating the blade element momentum (BEM) theory and finite element method (FEM), the DLFSI model facilitates comprehensive predictions of how composite blades will perform in real-world conditions. With this approach, we have achieved substantial improvements in critical performance metrics such as the power coefficient (a measure of energy conversion efficiency) and the maximum equivalent stress (a key indicator of structural integrity). The innovative DLFSI model presented in this study holds the potential for practical application within the realm of tidal turbine design and is poised to catalyze the sustainable progression of renewable energy technologies.

Experimental study of the upstream bathymetry effects on a ducted twin vertical axis turbine

Tidal turbines at sea are subject to complex flow conditions. Among that complexity, wide bathymetry obstacles can generate powerful coherent flow structures whose impact on horizontal axis tidal turbines was proved to be highly detrimental. Consequently, the present paper aims at studying the effects of such coherent flow structures on the response of another tidal turbine geometry, namely a bottom-mounted ducted twin vertical axis tidal turbine (2-VATT). We tested a 1/20 scale model of such a 2-VATT in Ifremer’s flume tank either with a flat bed or downstream of a wide bathymetry obstacle at a constant far upstream velocity and we measured the turbine response simultaneously with the flow velocity. These flow measurements make it possible to compute cross-correlations in order to analyse the influence of the velocity fluctuation on the turbine response. The results reveal a strong drop in the average power and loads coefficients of the 2-VATT combined with significantly larger fluctuation. The velocity deficit and the high level of turbulence in the obstacle wake is responsible for a 40% lower average power coefficient and more than 3 times higher standard deviation compared to the flat bed configuration. The loads standard deviations are multiplied by 2 for the drag and by 10 for the lift when the 2-VATT is downstream of the bathymetry obstacle. This behaviour strongly increases the risks of structural fatigue failure, but the turbine drifting or overturning risks under those conditions remain lower than with the flat bed. The power fluctuation increase appears to be mostly due to the flow shear in the obstacle wake whereas the load fluctuation is mostly due to the periodical passing of the coherent flow structures. Thus, a proper characterisation of the flow at each precise turbine locations prior deployment at sea is highly recommended to design their structure accordingly.

On the necessity of considering the hub when examining the induction of a horizontal axis tidal turbine

The induction models developed for wind turbines are not suitable for tidal turbines. The main reason is related to the differences in the ratio of the hub diameter to the rotor diameter, much more important in the case of tidal turbines. Thus, the hub contribution cannot be ignored. Furthermore, the specificities of the flow that impacts the turbine (strong shear) have to be taken into account contrary to a supposedly uniform upstream flow. To address these challenges, a new analytical induction model is proposed that combines both models related to the rotating blade and the hub effect. The effectiveness of the new model is evaluated against a specific experimental database for which a scale horizontal axis tidal turbine is placed in several representative turbulent shear flows. Particle Image Velocimetry measurements are synchronized with turbine thrust measurements to analyze the modifications of the mean velocity fields as a function of the thrust coefficient. The comparison shows that, regardless of the turbine rotational speed and/or the nature of the incoming shear velocity profile, the new model is in good agreement with the experimental results. Therefore, this result is very important for numerical modeling of the flow around the tidal turbines.

The effects of vortex generators on the characteristics of the tip hydrofoil and the horizontal axis tidal turbine blade

The blade of horizontal axial tidal turbine (HATT) will experience unsteady characteristics, such as dynamic stall, hysteresis loop, and stall delay, leading to unsteady loads that challenge its performance and survivability in the complex ocean environment with turbulent flow, waves, and shear flow. Installing vortex generators (VGs) on the blade surface effectively controls flow separation and improves the performance of the HATT blades. However, most existing VGs studies focus on two-dimensional models that do not consider the tip vortex, requiring further research to investigate the influence of VGs on the blade tip and their potential benefits. This study investigates the static and dynamic effects of different VGs parameters on the NACA63820 hydrofoil installed at the tip through hydrofoil water tunnel experiments and numerical simulations to understand the advantages of using VGs in this configuration. The results show that VGs alter the pressure distribution on the hydrofoil's surface, leading to the formation of pressure humps in the pressure curve of the hydrofoil section. The number and orientation of these humps depend on the openings of the VGs. This study comprehensively analyzes the factors causing these humps and their effects. In conclusion, installing appropriate VGs at the tip significantly improve the hydrofoil's performance and reduce the size of the hysteresis loop opening. Comparing different VGs identifies optimal parameters for HATT blades and evaluate their performance through numerical simulations. The results show that installing VGs at the 30% chord position of the airfoil section can improves the power coefficient by 1.6% at the optimal blade tip speed and broadens the operating range of the HATT.

Evaluating Mechanical Strength in Vertical-Axis Tidal Turbines: A Comparative Study of Internal Blade Structure and Material Selection through CFD Simulation

Due to the density of water, tidal turbine blades are subject to significantly greater stresses than wind turbine blades. Multiple blade failures occurred during prototype testing as a result of loading conditions and protracted exposure to seawater, which created a severe work environment. The structural integrity of tidal turbine blades is essential for long-term reliability and performance. Numerous investigations into structural performance have been conducted. However, previous research has centred on horizontal-axis tidal turbines, while research on small-scale vertical-axis tidal turbines is limited. This paper aims to compare the Vertical-Axis Tidal Turbine (VATT) structural performance of hollow and solid blade structures in an identical NACA profile using three distinct materials. Finite element analysis (FEA) is employed to construct a model and simulate the mechanical characteristics of VATT blades. The use of static analysis simulation is employed in order to evaluate many parameters, including stress distribution and deflection. Parametric studies are conducted to explore the impact of internal blade structure and materials on mechanical strength. The use of computational fluid dynamics (CFD) simulations is employed for the purpose of analyzing the interaction between blades of vertical axis tidal turbines (VATT) and tidal currents, thereby enabling the assessment of structural loading. According to the simulation results, the hollow profile is subject to significant deflections and stresses. Other data indicates that the utilization of stiffeners in porous structures improves material efficiency and results in lighter blades, although further analysis is needed to investigate fatigue life prediction in optimizing structural design.

Numerical Investigation on Hydrodynamic Performance of a Horizontal Axis Tidal Current Turbine

Numerical Investigation on Hydrodynamic Performance of a Horizontal Axis Tidal Current Turbine

Generation and distribution of turbulence-induced loads fluctuation of the horizontal axis tidal turbine blades

Horizontal axis tidal turbines (HATTs) working in a complex flow environment will encounter unsteady streamwise flow conditions that affect their power generation and structural loads, where power fluctuations determine the quality of electricity generation, directly affecting the grid and reliability of the power transmission system; fatigue loads affect various structures and mechanical components of the turbine, directly determining the lifespan and reliability of the turbine. To gain insight into the generation mechanism and distribution of these excitations, a large eddy simulation is employed to analyze the inflow turbulence and unsteady forces excitations by a three-blade HATT. A spectral synthesizer was used to generate incoming turbulence flow. The strip method was applied on the HATT by dividing the blade into 20 strips. The thrust received by each strip and the flow velocity upstream and downstream of the blade's root, middle, and tip were monitored. The distribution of unsteady loads on the blades was analyzed, as well as the relationship between flow velocity upstream and downstream of the blade and the unsteady characteristics of the blades. The simulation results show that the unsteady hydrodynamic fluctuations of the HATT blades reach up to 57.44% under a turbulent intensity of 10%. Through intuitive analysis of flow separation on the suction surface of the blade at various moments under a low tip speed ratio, we can comprehend the variations in inflow velocity and flow separation on the blade surface. Analyzing the distribution of blade load from root to tip reveals that the maximum load values are concentrated in the 14th–16th strips, corresponding to the region from 0.7R to 0.8R. Moreover, the middle and tip sections of the blades predominantly contribute to the harmonics of the 3BPF (blade passing frequency) and broadband, with the middle section making a greater contribution. The tip section primarily contributes to harmonics above 3BPF. This research want to makes a valuable contribution to the comprehensive understanding of turbulence-induced exciting forces and the practical engineering design of HATT.

A model for predicting the unsteady hydrodynamic characteristics on the blades of a horizontal axis tidal turbine

Tidal current turbines operate in a highly turbulent environment, which results in significant fluctuations in unsteady loads and consequent fatigue and dynamic failures in the rotor. Therefore, accurate calculation of these unsteady loads is crucial. However, the existing models do not take into account the influence of varying relative blade section thickness on dynamic stall when predicting the unsteady characteristics of horizontal axis tidal turbine (HATT) blades. To forecast the unsteady characteristics of the HATT blades, this study developed a method that considers the influence of relative blade thickness on dynamic stall. The modified Leishman-Beddoes (L-B) dynamic stall model, 3D rotational augmentation model, and steady-state BEM model were combined to predict the unsteady hydrodynamic characteristics of blades by synthesizing the transient inlet velocities induced by waves, shear flow and turbulence. In this method, the static parameters required for the modified L-B dynamic stall model were calculated by XFOIL within a range of small angle of attack (AoA) and then extrapolated to cover the entire range of AoA using the Viterna extrapolation method. The required dynamic parameters were obtained by CFD numerical simulation. This method, that we call HATT-UCPM, can consider both the effects of a single element on the unsteady hydrodynamic characteristics of the blades, as well as the combined effects of shear flow, waves, and turbulence on the blades in the actual marine environment. The accuracy of the method was validate through CFD numerical simulation. The results showed that the proposed method has a high consistency with the numerical simulation results, indicating that it has a good accuracy in the prediction of unsteady characteristics of HATT blades. Finally, the study examined several cases to investigate the impacts of shear flow, waves, and turbulence on the unsteady loads of blades, both individually and in combination.

A parametric analysis of the performance of a horizontal axis tidal current turbine for improving flow-converging effect

This paper proposed a research method for secondary design and parametric analysis of the contraction section of the shroud to improve the flow-gathering effect of horizontal axis tidal current turbines. By comparing the velocity ratio, drag coefficient, and flow field stability of the nine different shroud profile types, a conclusion was drawn that the hydrodynamic performance of the exponential (Type-A) shroud is best. On this basis, the primary parametric analysis of the A profile type shroud is carried out by changing the contraction ratio of the shroud's contraction section to divide the profile into three parts. The results show that the vertical flange inhibits the flow-gathering effect of the shroud, so the secondary parametric analysis is proceeded by removing the flange and changing the flange inclination angle, respectively. At the contraction ratio of 6/8, the flow-gathering effect of each shroud is best, among which the hydrodynamic performance of Type-ABL-6-85° shroud with the flange inclination angle of 85° is best. The maximum power coefficient (Cpmax) is 43.20%, which is 31.59% higher than that with Type-A shroud when the tip speed ratio is 1.5. Therefore, it can be considered that the combined profile type of the shroud contraction section has a better flow-gathering effect than the single profile type.