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Biofouling, the accumulation of marine organisms on submerged surfaces, presents significant operational challenges across various marine industries. Traditional detection methods are labor intensive and costly, necessitating the development of automated systems for efficient monitoring. The study presented in this paper focuses on detecting biofouling on tidal stream turbine blades using camera-based monitoring. The process begins with dividing the video into a series of images, which are then annotated to identify and select the bounding boxes containing objects to be detected. These annotated images are used to train YOLO version 8 to detect biofouled and clean blades in the images. The proposed approach is evaluated using metrics that demonstrate the superiority of this YOLO version compared to previous ones. To address the issue of misdetection, a data augmentation approach is proposed and tested across different YOLO versions, showing its effectiveness in improving detection quality and robustness. [ABSTRACT FROM AUTHOR]

This paper addresses the issues of maximum power point tracking (MPPT) and fault-tolerant control in tidal steam turbines under complex marine environments. In order to solve the conflicting problems in the existing sliding mode control between dynamic performance and chatter reduction as well as the use of fault estimation link in the fault-tolerant control, which increases the system complexity, an adaptive non-singular fast terminal sliding mode and adaptive robust fault tolerance method (ANFTSMC-ARC) is proposed. First, a speed controller equipped with adaptive non-singular fast terminal sliding mode control (ANFTSMC) is designed to improve the power capture efficiency under swell disturbances. This design achieves fast convergence and circumvents the singularity problem. Then, a new reach law is proposed based on the adaptive hybrid exponential reaching law (AHERL), which ensures high tracking performance while reducing chattering. In addition, considering that the hydraulic pitch system is prone to failure, a fault-tolerant controller with automatically adjustable gain is designed under the adaptive robust scheme. With the help of Lyapunov theory, the closed-loop system is proved to be uniform and ultimately bounded. Finally, comparative simulation results verify the efficiency of the proposed control strategy. [ABSTRACT FROM AUTHOR]

Biofouling, the accumulation of marine organisms on submerged surfaces, presents significant operational challenges across various marine industries. Traditional detection methods are labor intensive and costly, necessitating the development of automated systems for efficient monitoring. The study presented in this paper focuses on detecting biofouling on tidal stream turbine blades using camera-based monitoring. The process begins with dividing the video into a series of images, which are then annotated to identify and select the bounding boxes containing objects to be detected. These annotated images are used to train YOLO version 8 to detect biofouled and clean blades in the images. The proposed approach is evaluated using metrics that demonstrate the superiority of this YOLO version compared to previous ones. To address the issue of misdetection, a data augmentation approach is proposed and tested across different YOLO versions, showing its effectiveness in improving detection quality and robustness.

Tidal stream turbines (TSTs) harness the kinetic energy of tides to generate electricity by rotating the rotor. Biofouling will lead to an imbalance between the blades, resulting in imbalanced torque and voltage across the windings, ultimately polluting the grid. Therefore, rotor condition monitoring is of great significance for the stable operation of the system. Image-based attachment detection algorithms provide the advantage of visually displaying the location and area of faults. However, due to the limited availability of data from multiple machine types and environments, it is difficult to ensure the generalization of the network. Additionally, TST images degrade, resulting in reduced image gradients and making it challenging to extract edge and other features. In order to address the issue of limited data, a novel non-data-driven edge detection algorithm, indexed resemble-normal-line guidance detector (IRNLGD), is proposed for TST rotor attachment fault detection. Aiming to solve the problem of edge features being suppressed, IRNLGD introduces the concept of "indexed resemble-normal-line direction" and integrates multi-directional gradient information for edge determination. Real-image experiments demonstrate IRNLGD's effectiveness in detecting TST rotor edges and faults. Evaluation on public datasets shows the superior performance of our method in detecting fine edges in low-light images. [ABSTRACT FROM AUTHOR]

The style of the underwater images varies according to the region of the sea. However, Tidal Stream Turbine (TST) rotor images captured in the laboratory environment cannot reflect the real underwater environment in image style, resulting in poor generalization of image signal-based fault detection algorithms. Due to the fixed capture position of the camera, the TST rotor image dataset has a high semantic similarity between images, resulting in content loss in conventional image-to-image translation networks. Meanwhile, the one-to-one translation feature in other works cannot meet our requirements. In this work, a Domain Variable Prior-based Multi-style Transfer Network (DVP-MSTN) is proposed to achieve TST rotor image style augmentation. First, the backbone network is trained using a public paired dataset to acquire prior knowledge of domain variable (Knowledge Acquiring, KA). Next, a Multi-domain Transfer Unit (MDT unit) is introduced to enable the conversion of style representations in low-dimensional space. Finally, the prior knowledge is shared to train the MDT unit by fixing the parameters of the backbone network optimized from the KA process (Knowledge Sharing, KS). In addition, an algorithm based on the dark channel of the image is proposed to improve the transfer of low-contrast features. Specifically, a discriminator is used to discriminate the image dark channel to guide the MDT unit to generate low-contrast style representation conditionally. Meanwhile, color loss is employed to preserve the color feature of the image. By controlling the weights of the style code, this method enables control over the image style transfer process, thereby expanding the variety of image styles in the dataset for the purpose of data augmentation. [ABSTRACT FROM AUTHOR]

Renewable energy generation is increasingly important due to serious energy issues. A Doubly Salient Permanent Magnet Generator (DSPMG) can be an interesting candidate for tidal stream renewable energy systems. However, the special structure makes the system nonlinear and strongly coupled even after Park transformation and involves a larger torque ripple. Previous research mainly focused on model-based control for this machine, which is very sensitive to the parameters. Thus, to control the complex systems stably and accurately, two model-free control algorithms, Active Disturbance Rejection-Based Iterative Learning Control (ADRILC) and Active Disturbance Rejection Control–Iterative Learning Control (ADRC–ILC), are proposed for the current and speed control loops of a DSPMG-based Tidal Stream Turbine (TST), respectively. ADRC–ILC uses ADRC to deal with the external non-periodic speed ripple and adopts ILC to reduce the internal periodic speed ripple. ADRILC employs an iterative method to improve the ESO for the enhancement of the convergence rate of ILC. Considering the variable tidal speed, when the speed is above the rated value, Maximum Power Point Tracking (MPPT) must be changed to a power limitation strategy for limiting the generator power to the rated value and extending the system operating range. Thus, Optimal Tip Speed Ratio (OTSR)-based MPPT (for a low tidal current speed) and Leading Angle Flux-Weakening Control (LAFWC) (for a high tidal current speed) strategies are also proposed. According to the simulation results, the proposed ADRC–ILC + ADRILC has the lowest torque ripple, the highest control accuracy, as well as a good current tracking capability and strong robustness. At the rated speed, the proposed method reduces the torque ripple by more than 20% and the speed error by about 80% compared with PI control: the current difference is limited in 2A. The LAFWC proposed for an excessive tidal current speed is effective in conserving the electromagnetic power and increasing the generator speed. [ABSTRACT FROM AUTHOR]

This paper has developed an operation and maintenance (O&M) model for projected 20 MW tidal stream farm case studies at two sites in the northeast Atlantic in France and at EMEC's Fall of Warness site in the UK. The annual energy production, number of incidents, and downtimes of the farms for corrective and planned (preventive) maintenance strategies are estimated using Monte Carlo simulations that vary weather windows, repair vessel availabilities, and mean annual failure rates modelled by Weibull distributions. The trade-offs between the mean annual failure rates, time availability, O&M costs, and energy income minus the variable O&M costs were analysed. For all scenarios, a 5-year planned maintenance strategy could considerably decrease the mean annual failure rates by 37% at both sites and increase the net energy income. Based on a detailed sensitivity analysis, the study has suggested a simple decision-making method that examines how the variation in the mean annual failure rate and changes in spare-part costs would reduce the effectiveness of a preventive maintenance strategy. This work provides insights into the most important parameters that affect the O&M cost of tidal stream turbines and their effect on tidal energy management. The output of the study will contribute to decision-making concerning maintenance strategies. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper addresses the issues of maximum power point tracking (MPPT) and fault-tolerant control in tidal steam turbines under complex marine environments. In order to solve the conflicting problems in the existing sliding mode control between dynamic performance and chatter reduction as well as the use of fault estimation link in the fault-tolerant control, which increases the system complexity, an adaptive non-singular fast terminal sliding mode and adaptive robust fault tolerance method (ANFTSMC-ARC) is proposed. First, a speed controller equipped with adaptive non-singular fast terminal sliding mode control (ANFTSMC) is designed to improve the power capture efficiency under swell disturbances. This design achieves fast convergence and circumvents the singularity problem. Then, a new reach law is proposed based on the adaptive hybrid exponential reaching law (AHERL), which ensures high tracking performance while reducing chattering. In addition, considering that the hydraulic pitch system is prone to failure, a fault-tolerant controller with automatically adjustable gain is designed under the adaptive robust scheme. With the help of Lyapunov theory, the closed-loop system is proved to be uniform and ultimately bounded. Finally, comparative simulation results verify the efficiency of the proposed control strategy.

Tidal stream turbines (TSTs) harness the kinetic energy of tides to generate electricity by rotating the rotor. Biofouling will lead to an imbalance between the blades, resulting in imbalanced torque and voltage across the windings, ultimately polluting the grid. Therefore, rotor condition monitoring is of great significance for the stable operation of the system. Image-based attachment detection algorithms provide the advantage of visually displaying the location and area of faults. However, due to the limited availability of data from multiple machine types and environments, it is difficult to ensure the generalization of the network. Additionally, TST images degrade, resulting in reduced image gradients and making it challenging to extract edge and other features. In order to address the issue of limited data, a novel non-data-driven edge detection algorithm, indexed resemble-normal-line guidance detector (IRNLGD), is proposed for TST rotor attachment fault detection. Aiming to solve the problem of edge features being suppressed, IRNLGD introduces the concept of “indexed resemble-normal-line direction” and integrates multi-directional gradient information for edge determination. Real-image experiments demonstrate IRNLGD’s effectiveness in detecting TST rotor edges and faults. Evaluation on public datasets shows the superior performance of our method in detecting fine edges in low-light images.

This article deals with the techno-economic optimal sizing of a tidal stream turbine (TST)–battery system. In this study, the TST system consists of a turbine rotor and a permanent magnet synchronous generator (PMSG) associated with a three-phase converter coupled to a DC bus. A battery is used within the system as an energy storage system to absorb excess produced power or cover power deficits. To determine the optimal sizing of the system, an iterative approach was used owing to its ease of implementation, high accuracy, and fast convergence speed, even under environmental constraints such as swell and wave effects. This technique is based on robust energy management, and the recursive algorithm includes the deficiency of power supply probability (DPSP) and the relative excess power generation (REPG) as technical criteria for the system reliability study, and the energy cost (EC) and the total net present cost (TNPC) as economic criteria for the system cost study. As data inputs, the proposed approach used the existing data from the current speed profile, the load, and economic parameters. The desired output is the system component optimal sizing (TST power, and battery capacity). In this paper, the system sizing was studied during a one-year time period to ensure a more reliable and economical system. The results are compared to well-known methods such as genetic algorithms, particle swarm optimization, and software-based (HOMER) approaches. The optimization results confirm the efficiency of the proposed approach in sizing the system, which was simulated using real-world tidal velocity data from a specific deployment site. [ABSTRACT FROM AUTHOR]

This paper describes resilient controls of a PMSM-based Tidal Stream Turbine (TST) with inter-turn faults. In this context, a simple dynamic model, derived for the Permanent Magnet Synchronous Machine (PMSM) with inter-turn fault, shows that traditional methods such as Proportional Integrator (PI) controllers are not effective in the case of a fault presence. So, the TST performances present a significant degradation. Therefore, the second-order sliding mode and the backstepping techniques have been adopted as fault-tolerant control approaches to address the robustness problem. TST system simulation under an inter-turn fault is evaluated and discussed using real tidal velocities of the Raz de Sein site in Bretagne, France. [ABSTRACT FROM AUTHOR]

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 and the wake recovery. 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. [ABSTRACT FROM AUTHOR]

This study addresses the biofouling challenges in Tidal Stream Turbines (TSTs) to ensure their reliable and optimal operation. In this context, it is proposed an effective methodology employing a soft voting ensemble transfer learning-based approach for the detection and extent classification of biofouling. The proposed framework incorporates essential components such as data augmentation and pre-processing, including image resizing and data segmentation, forming a comprehensive video image-based approach. To overcome the constraint of limited data, experimental investigations were conducted, resulting in the acquisition of two datasets: one from the TST platform at Shanghai Maritime University (SMU) and the other from the tidal turbulence test facility at Lehigh University (LU). The three prominent convolutional neural network models, namely Visual Geometry Group (VGG), Residual Network (ResNet) and MobileNet, trained on these datasets, demonstrate precise detection and classification of turbine conditions, achieving an accuracy of 83% for the SMU dataset and 90% for the LU dataset. The noted disparity in accuracy for the SMU dataset is attributed to its smaller size, highlighting the significant impact of dataset scale on classification performance. This study provides valuable insight into the development of effective biofouling detection and classification strategies for TST systems. • Provide a soft voting ensemble transfer learning-based tool for real-time biofouling detection and estimation. • Data augmentation using rotation, scaling, flipping, zooming, and brightening of the cropped input images. • Data pre-processing including image resizing and data segmentation using the segment anything model. [ABSTRACT FROM AUTHOR]

Harnessing the power of tidal streams is a sustainable way of exploiting renewable marine energy resources. It involves installing tidal stream turbines underwater to harness the energy. Nevertheless, these turbines are prone to the accumulation of biofouling, which significantly reduces their energy output and operational efficiency. It is therefore crucial to implement a condition-based monitoring system to detect biofouling promptly and ensure the continuous operation of a tidal stream turbine. In this context, this paper presents a data-centric approach that uses model submerged tidal stream turbine video images to detect and quantify biofouling. The relevance of a two-dimensional variational mode decomposition approach is investigated to extract relevant information from the potentially noisy collected images. While generative adversarial networks are used to address the data imbalance problem, a convolutional neural network is adopted to detect and assess the extent of biofouling. The performance of the proposed approach is assessed and validated using two experimental datasets obtained from the tidal stream turbine platforms of the Shanghai Maritime University and the Lehigh University. • Intelligent decision support tool for real-time biofouling detection and estimation. • Data augmentation using GAN for synthetic image generation. • Underwater image denoising using 2D-VMD for better detection of biofouling. • Multi-scale function extraction with ResNet50 to distinguish most discriminating class features. [ABSTRACT FROM AUTHOR]

Renewable energy generation is increasingly important due to serious energy issues. A Doubly Salient Permanent Magnet Generator (DSPMG) can be an interesting candidate for tidal stream renewable energy systems. However, the special structure makes the system nonlinear and strongly coupled even after Park transformation and involves a larger torque ripple. Previous research mainly focused on model-based control for this machine, which is very sensitive to the parameters. Thus, to control the complex systems stably and accurately, two model-free control algorithms, Active Disturbance Rejection-Based Iterative Learning Control (ADRILC) and Active Disturbance Rejection Control–Iterative Learning Control (ADRC–ILC), are proposed for the current and speed control loops of a DSPMG-based Tidal Stream Turbine (TST), respectively. ADRC–ILC uses ADRC to deal with the external non-periodic speed ripple and adopts ILC to reduce the internal periodic speed ripple. ADRILC employs an iterative method to improve the ESO for the enhancement of the convergence rate of ILC. Considering the variable tidal speed, when the speed is above the rated value, Maximum Power Point Tracking (MPPT) must be changed to a power limitation strategy for limiting the generator power to the rated value and extending the system operating range. Thus, Optimal Tip Speed Ratio (OTSR)-based MPPT (for a low tidal current speed) and Leading Angle Flux-Weakening Control (LAFWC) (for a high tidal current speed) strategies are also proposed. According to the simulation results, the proposed ADRC–ILC + ADRILC has the lowest torque ripple, the highest control accuracy, as well as a good current tracking capability and strong robustness. At the rated speed, the proposed method reduces the torque ripple by more than 20% and the speed error by about 80% compared with PI control: the current difference is limited in 2A. The LAFWC proposed for an excessive tidal current speed is effective in conserving the electromagnetic power and increasing the generator speed.

Developing reliable tidal-energy turbines of a large size and capacity links to preservation of the structural safety and stability of the blades. In this study, a bidirectional fluid–structure coupling method was applied to analyze the hydrodynamic performance and structural characteristics of the blade of a tidal-stream turbine. Analyses were conducted on the transient and stable structural stresses, fatigue, and deformations under the influence of water depth and turbine rotational speed. The performance predictions with and without fluid–structure coupling are similar to measurements. The water-depth change has little effect on the stress and deformation change of the blade, while the turbine-speed change has the most significant effect on it. When the turbine just starts, the blade will be subject to a sudden change load. This is due to the increase in turbine speed, resulting in the sudden load. Similar to the trend of blade stress, the blade safety factor is lower near the root of the blade, and the turbine-speed change has a more significant impact on the blade structure's safety. However, the number of stress cycles in the blade at different rotational speeds is within the safety range. [ABSTRACT FROM AUTHOR]

Power extraction has become a critical consideration in tidal stream turbine (TST) systems. In practice, the lumped disturbances under varying tidal current conditions may deteriorate the maximum power point tracking (MPPT) performance and cumulate fatigue damage over-rated power. Besides, the conventional pitch controllers are sensitive to parameter uncertainties of the nonlinear TST system. In this paper, a novel output power internal control strategy based on pseudo-tip-speed ratio and adaptive genetic algorithm (PTSR-AGA) is proposed to improve the anti-interference ability and reliability. The proposed control scheme consists of two parts. The first part proposes the PTSR method for MPPT to predict the TST's operating point which contributes reducing the logical errors assigned to swell disturbances. The second part designed an AGA for the optimization of the pitch controller to conduct its angle delay. A reduced pitch control strategy is applied to the preprocessing of the pitch controller to reduce the mechanical wear over the rated power. The comparative simulation results validate the TST system can obtain a higher power efficiency of energy capture and a smoother power output with the proposed control strategies at full range of tidal current speed. [ABSTRACT FROM AUTHOR]

Study on the performance of the tidal stream turbines could greatly improve tidal stream energy development. Up to date, few studies about the twin-rotor horizontal axis tidal turbines (TRHATTs) are available. In this study, laboratory experiments with a range of approaching flow velocity and yaw angles are conducted to investigate the wake structures in the lee side of the turbine. The experimental results show that there are three 'rod-liked' wakes behind the turbine, which merge into one wake further downstream. Increase of the approaching flow velocity can accelerate wake velocity recovery and enhances turbulence intensity. Correspondingly, the thrust and the fluctuation of thrust also increase. When the turbine is subjected to the yawed inflow, one side of the near wake mixing accelerates and the turbulence intensity distribution becomes asymmetric. The study shows that the thrust is slightly reduced with an increase of the yaw angle, and reaches the maximum when the yaw angle is 40°. Fluctuation range of the thrust increases with the increase of the yaw angle, and starts to decrease when the yaw angle exceeds 30°. • The thrust on the turbine decreases gradually with the increasing yaw angle. • There are three 'rod-liked' wakes behind the twin-rotors and the mono-pile. • Wake velocity and turbulence intensity vary sharply within 4D downstream. • The yaw angle affects the shape of wake and recovery of wake velocity. [ABSTRACT FROM AUTHOR]

In the Marine environment, waves and turbulence usually coexist, affecting the operation performance of the tidal current energy turbine. This paper conducts experiments on a scaled tidal stream turbine to study the wave period effect on the wake and power characteristics. Under a wave-current environment, the wake is found to display Gaussian distribution. Within the 4 times diameter downstream range (4D), the turbulence is significant, and both the wake velocity loss and fluctuation increase first and then decrease with wave period. After 6D, the flow field gradually recovers to the inflow level. The wave period affects the transversal turbulence, more in the near than far wake region, as the significant turbulence intensities at the hub and blade tips gradually merge and become consistent after 6D. The wave period affects little the power coefficient C P owing to the sinusoidal inflow velocity nature. However, the amplitude of the phase average power increases first and then decreases with the wave period. By contrast, the phase average power fluctuations are sensitive to cycle changes only within the low TSR interval; they decrease sharply with TSR. In addition, the energy distribution of power fluctuation in the wave flow coupling environment is mainly concentrated at the sum and difference, and as well multiples, of the rotational and wave frequency. The wave and its multiples energy distribution increases and then decreases with the wave period. The highlights of this work are summarized as follows. • The wave displays a Gaussian distribution under wave-current states. • The change of mean power coefficient with waves is insignificant. • The period of waves alters significantly the near-wake transversal turbulence distribution. • The turbine output energy is concentrated in the wave frequency. [ABSTRACT FROM AUTHOR]

This paper has developed an operation and maintenance (O&M) model for projected 20 MW tidal stream farm case studies at two sites in the northeast Atlantic in France and at EMEC’s Fall of Warness site in the UK. The annual energy production, number of incidents, and downtimes of the farms for corrective and planned (preventive) maintenance strategies are estimated using Monte Carlo simulations that vary weather windows, repair vessel availabilities, and mean annual failure rates modelled by Weibull distributions. The trade-offs between the mean annual failure rates, time availability, O&M costs, and energy income minus the variable O&M costs were analysed. For all scenarios, a 5-year planned maintenance strategy could considerably decrease the mean annual failure rates by 37% at both sites and increase the net energy income. Based on a detailed sensitivity analysis, the study has suggested a simple decision-making method that examines how the variation in the mean annual failure rate and changes in spare-part costs would reduce the effectiveness of a preventive maintenance strategy. This work provides insights into the most important parameters that affect the O&M cost of tidal stream turbines and their effect on tidal energy management. The output of the study will contribute to decision-making concerning maintenance strategies.

The impact fault caused by ocean creatures poses a risk to the safe operation of tidal stream turbine blades. However, it is difficult to detect the weak impact fault directly because the collected signal is disturbed by the waves, turbulence, and continuously variable flow velocity. To solve this problem, a fusion method of feature sample screening and local outlier factor is proposed in this paper. This method consists of three main parts. First, the Teager–Kaiser energy operator and the sliding window technique are introduced to extract the envelope statistical features from the current signal. Second, a parameter optimized density-based spatial clustering of applications with noise (DBSCAN) algorithm is proposed to perform feature sample screening before detecting. Notably, the conventional DBSCAN algorithm is sensitive to the parameter selection and lacks the capability of adaptive screening, so this paper proposes an adaptive sand cat swarm optimization algorithm to optimize the parameters. Finally, the local outlier factor is utilized to detect faults based on the screened feature samples. The experimental results show that the proposed method stands out in reducing the false alarm rate compared with traditional methods. Specifically, within the flow velocity ranges of 1.0–1.3 m/s and 1.3–1.6 m/s, the false alarm rates can reach 0% and 0.17%, respectively. [ABSTRACT FROM AUTHOR]

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.

Malaysia has a great potential to harness energy in water due to its long coastline within the South China Sea and the Straits of Malacca. Malaysia’s energy mix could be improved using marine current energy devices (MCEDs) to replace fossil fuel and it is predictable energy compare to hydropower, solar photovoltaic (PV), and biomass. However, MCEDs is not been fully developed in Malaysia. The objectives of this paper are to provide a useful background for policymakers or researchers in the types of MCEDs and potential sites location of MCEDs that are applicable in Malaysia. This review also discusses the issues and challenges of MCEDs in Malaysia. Five types of MCEDs were discussed including tidal range device, tidal stream turbine, wave energy converter, ocean thermal energy conversion, and salinity gradient energy. These MCEDs are compared for their suitability of application in Malaysia. Among all MCEDs, tidal stream turbine is identified as high potential and commercially viable in Malaysia. However, ocean characteristics in Malaysia are low kinetic energy-flux density, low current speed, low tide, and shallow water; only fulfill the minimum requirement of tidal stream turbine making the tidal stream energy resources not significant enough to contribute to the nation’s energy mix. Therefore, using diffuser augmented tidal stream turbines to increase the flow velocity should be studied thoroughly.

Recently, the output of Computational Fluid Dynamic (CFD) prediction on tidal stream turbine systems has been receiving great attention owing to the vast and untapped tidal stream potential. For several years, many publications have documented the accuracy of CFD methods for steady flows, but not for unsteady flows. A challenging area persisting in the computational field is its dependence on large computing resources, and the unsteady nature of usual tidal streams. To overcome this problem, researchers have proposed modelling simpler, representative devices or combined CFD with alternative predictive methods. Nevertheless, the turbulent modelling has been a critical issue in the CFD methods and great effort has been devoted to the study of turbulence and wave effect on the wake and functioning of the turbine. The present paper is a review of CFD application on tidal stream turbine performance in both steady and unsteady flows. The performance of the turbine predicted by actuator and blade resolved methods, has been in accordance with laboratory observations. Findings of the wake have been both consistent and inconsistent with measurements, arising from interpretation of the blade force, fluid-solving method and onset flow model, and downstream range distance. With regards to arrays, preliminary work shows turbine arrangement can have profound effects in the onset flow, and in consequence, the performance of adjacent turbine rows. The results reported appear to support the wind similarity assumption, such as wake Gaussian velocity distributions and fluctuating turbine output in unsteady flows. Under the influence of surface waves, the wake recovers faster than steady flow condition due to the flow's convective acceleration, but the mean performance stays almost equal. The findings in this paper give a critical review and insight of important implications for future turbine research, such as experimental validation of the turbine prediction output in small and large arrays.

This article deals with the techno-economic optimal sizing of a tidal stream turbine (TST)–battery system. In this study, the TST system consists of a turbine rotor and a permanent magnet synchronous generator (PMSG) associated with a three-phase converter coupled to a DC bus. A battery is used within the system as an energy storage system to absorb excess produced power or cover power deficits. To determine the optimal sizing of the system, an iterative approach was used owing to its ease of implementation, high accuracy, and fast convergence speed, even under environmental constraints such as swell and wave effects. This technique is based on robust energy management, and the recursive algorithm includes the deficiency of power supply probability (DPSP) and the relative excess power generation (REPG) as technical criteria for the system reliability study, and the energy cost (EC) and the total net present cost (TNPC) as economic criteria for the system cost study. As data inputs, the proposed approach used the existing data from the current speed profile, the load, and economic parameters. The desired output is the system component optimal sizing (TST power, and battery capacity). In this paper, the system sizing was studied during a one-year time period to ensure a more reliable and economical system. The results are compared to well-known methods such as genetic algorithms, particle swarm optimization, and software-based (HOMER) approaches. The optimization results confirm the efficiency of the proposed approach in sizing the system, which was simulated using real-world tidal velocity data from a specific deployment site.

Developing reliable tidal-energy turbines of a large size and capacity links to preservation of the structural safety and stability of the blades. In this study, a bidirectional fluid–structure coupling method was applied to analyze the hydrodynamic performance and structural characteristics of the blade of a tidal-stream turbine. Analyses were conducted on the transient and stable structural stresses, fatigue, and deformations under the influence of water depth and turbine rotational speed. The performance predictions with and without fluid–structure coupling are similar to measurements. The water-depth change has little effect on the stress and deformation change of the blade, while the turbine-speed change has the most significant effect on it. When the turbine just starts, the blade will be subject to a sudden change load. This is due to the increase in turbine speed, resulting in the sudden load. Similar to the trend of blade stress, the blade safety factor is lower near the root of the blade, and the turbine-speed change has a more significant impact on the blade structure’s safety. However, the number of stress cycles in the blade at different rotational speeds is within the safety range.

Turbulent non-homogenous flow environments at high-energy tidal sites lead to variation in power performance of tidal stream turbines. In addition, non-uniform loading due to combined effects of shear and elevated inflow turbulence affects device survivability. In the current study, an active-grid turbulence generator is used to mimic sheared-turbulent inflow representative of the flood (low shear) and ebb tides (high shear). The performance and near-wake characteristics of a turbine model measured in the sheared-turbulent inflow conditions are compared to conditions where the flow velocity is uniform with low and elevated turbulence intensities (T i). The sheared-turbulent inflows were observed to result in a 5–15% drop in maximum power coefficient when compared to the low T i case. An increase of ∼30% in torque- and ∼50% in thrust- fluctuations were observed for sheared inflows. Unlike the near axisymmetric wake profiles observed for homogeneous cases, inflow shear was observed to incite asymmetry in the near-wake with an immediate impact in wake turbulence and a more gradual effect on the velocity deficit and integral length scales. The data sets are deemed valuable in calibrating computational models to better predict turbine response and optimize turbine efficiency and the complementing power take-off system. [Display omitted] [ABSTRACT FROM AUTHOR]

Most tidal energy site studies concentrate on resource size; few examine other factors that may be of equal or even greater importance in determining site feasibility for tidal turbine array deployments. These factors include aspects such as electrical grid proximity, water depth, the location of marine protected areas, pre-existing users, environmentally significant regions and other restrictions. Using these factors, a more holistic approach to site selection was conducted for Australian waters using a Multi-Criteria Evaluation (MCE) process. This MCE method uses standardized factors combined with weighted linear combinations to calculate a site suitability index, where each factor is multiplied by a weight of relative importance. A sensitivity analysis on the factor weighting was performed to ensure the suitable selection of weighting factors to reduce conformation bias. The developed MCE model identified three promising locations in Australia, with contiguous areas in regions to the north of Broome Western Australia of 534 km2, the Banks Strait region northeast of Tasmania of 67 km2, and the Clarence Strait located in the Northern Territory of <1 km2 found. Additional examinations of possible co-location of tidal energy devices with wind and wave energy were examined. • Site suitability of potential Australian tidal energy sites determined nationally. • Highly suitable areas identified near Broome and the Clarence and Banks Straits. • Co-location with wave and wind renewable energy devices assessed. [ABSTRACT FROM AUTHOR]

Consideration of tidal stream turbine (TST) interactions with the surrounding environment and the resultant local scour is vital for safe operation and maintenance. A numerical model with coupling actuator line method (ALM) and immersed boundary method (IBM) is developed for simulating hydrodynamics synchronously with the local scour process around the TST. The ALM is applied to treat the rotating turbine rotor while the sediment dynamics is integrated into the IBM to simulate the scouring morphology. The simulating performance of the proposed ALM-IBM coupling model is validated and demonstrated by modeling the mono-pile supported horizontal-axis TST upon scouring seabed under steady currents. The impact of the horizontal-axis rotating turbine rotor on the scour around the supporting mono-pile under steady currents is then investigated. The results show that the rotating rotor can accelerate near-seabed flow resulting in the enhanced equilibrium scour scale around the mono-pile. The contribution of the mono-pile on the equilibrium maximum scour depth is stronger than that of the rotating rotor under the clear-water condition. The existence of the mono-pile can enhance the local mass and momentum exchanges between the wake- and surrounding-flow fields, leading to the asymmetrical scoured seabed morphology. [Display omitted] • A numerical model is developed with coupling ALM-IBM. • Sediment dynamics and morphodynamics are integrated into ALM-IBM model. • Hydrodynamics upon scouring morphology around TST is accurately simulated. • Impact of rotating rotor on sediment scour around mono-pile is investigated. • Respective contributions of rotating rotor and mono-pile on scour are clarified. [ABSTRACT FROM AUTHOR]

Power extraction has become a critical consideration in tidal stream turbine (TST) systems. In practice, the lumped disturbances under varying tidal current conditions may deteriorate the maximum power point tracking (MPPT) performance and cumulate fatigue damage over-rated power. Besides, the conventional pitch controllers are sensitive to parameter uncertainties of the nonlinear TST system. In this paper, a novel output power internal control strategy based on pseudo-tip-speed ratio and adaptive genetic algorithm (PTSR-AGA) is proposed to improve the anti-interference ability and reliability. The proposed control scheme consists of two parts. The first part proposes the PTSR method for MPPT to predict the TST’s operating point which contributes reducing the logical errors assigned to swell disturbances. The second part designed an AGA for the optimization of the pitch controller to conduct its angle delay. A reduced pitch control strategy is applied to the preprocessing of the pitch controller to reduce the mechanical wear over the rated power. The comparative simulation results validate the TST system can obtain a higher power efficiency of energy capture and a smoother power output with the proposed control strategies at full range of tidal current speed.

The horizontal axis turbine is one of the most promising energy extractors for tidal stream energy utilization. However, there is no widely accepted model for describing the wake structure of a tidal stream turbine. Besides, the flow velocity variation in wakes is accompanied by energy transformation and has hardly been investigated to date. In this paper, a brief review of existing laboratory tidal stream turbine experiments is first presented, followed by a discussion about the controlling variables that includes cross-comparisons between different results from physical laboratory tests. Theoretical derivation and experimental data analysis are conducted to enable a better understanding of the energy transformation and wake development processes, and tidal stream energy extraction. It has been found that part of the flow kinetic energy has been converted into potential energy before reaching the rotor, commonly used power coefficients are not equivalent when quantifying energy extraction, and it is possible to reconstruct turbine wakes using 3 independent data-based parameters. • Energy transformation from potential energy to kinetic energy occurs even before the flow reaching the rotor. • The widely used energy coefficients based on torque and thrust are not equivalent to each other. • It is possible to reproduce the horizontal and vertical far-wake velocity profiles using 3 independent parameters. [ABSTRACT FROM AUTHOR]

The tidal flow between bridge pillars and through open barriers is a promising source of ocean energy which can be exploited using tidal stream turbines, as proven recently by operational demonstration plants. The aim of this study is to clarify the consequences for the power output of tidal turbines when placing them in a hydraulic structure. To this end, experimental measurements of turbine power and wakes are performed, using a down-scaled turbine mounted at a submerged weir. The results are compared to an analytical model, validating its range of application for optimising turbine-weir geometries. The experimental data show that the power coefficient of the turbine can be increased by optimising the blockage of the channel and the distance between the turbine and the structure, which is related to the wake configuration. In this way, the power coefficient increased by 40% when the turbine was re-positioned from the upstream to the downstream end of the structure. The theoretical model could reproduce the measured power within 10% accuracy, proving its value as a rapid assessment tool. As such, this work advances the knowledge needed to meet targets on the transition towards renewable energy. • We present unique experimental data of turbine power and wakes. • Power output can be increased by 40% by optimising turbine position relative to a weir. • A theoretical performance model is validated with the data. • Schematising the wakes correctly is crucial to improve the model predictions. • The data reveal a geometry with high power output and small hydraulic resistance. [ABSTRACT FROM AUTHOR]

The presence of waves exposes tidal stream turbines to large and cyclic hydrodynamic loads which significantly influence the design requirements for tidal turbine blades. Here we describe a loading phenomenon not previously considered in literature caused as blades rotationally sample an oscillating and vertically decaying wave-induced velocity field. Although implicitly incorporated into numerical models, the dominant causes and relative influence have not previously been considered.In this article this effect is described through theoretical analysis and validated through scaled experiments; including irregular waves at angles to the rotor and current field. The associated loads are found to be strongly correlated to the wavenumber. The nature of the rotational-sampling-effect is confirmed through analysis of the experimental results, where characteristic sidebands are effectively predicted in the blade root bending moment spectra. It is estimated to account for between 8% and 16% of the fatigue damage and between 7% and 13% of the peak root bending moment for the conditions tested. A key finding is that two bilaterally-symmetrical oblique wave conditions do not produce equivalent loading patterns: one produces higher frequency oscillations. Additionally, it is found that the frequency of these loads reduces linearly with rotational speed; highlighting another consideration for tidal stream turbine operation. • Rotational sampling of wave-induced velocities by TST blades is described. • Theoretical description of sidebands developed and experimentally validated. • Bilaterally-symmetrical oblique wave conditions do not produce equivalent loads. • The process contributes 8–16% fatigue damage and 7–13% peak root bending moment. • Frequency of rotational sampling-based loads reduces linearly with rotational speed. [ABSTRACT FROM AUTHOR]

This paper describes a grid fault-resilient control approach for a grid-connected tidal stream turbine (TST) driven by a permanent magnet synchronous generator (PMSG). TSTs mainly use conventional PI controllers while they are very sensitive to grid faulty conditions. In this faulty context, the TST will experience power generation decrease and dynamic performance degradations. Indeed, the grid-side converter can be deactivated and the generator may be disconnected from the grid. Also, grid faults can make the system instable during and after faults occurrence, which can deteriorate the quality of the power injected into the grid from the TST generation system. In this paper, a resilient controller is therefore derived to enhance the PMSG-based TST performance during grid fault. In fact, high-order sliding modes have been adopted to sustain a minimum level of optimal performance and achieve a smoother gridinjected power in case of a grid fault. Simulations carried out on real tidal speed data measured at the Raz de Sein site in Bretagne in France clearly highlights proves the effectiveness of the proposed grid fault-resilient approach. [ABSTRACT FROM AUTHOR]

Blades of tidal stream turbines have to sustain many different loads during operation in the underwater environment, so securing their structural safety is a key issue. In this study, we focused on periodic loads due to wave orbital motion and propose a load reduction method with a blade design. The flap of an airplane wing is a well-known structure designed to increase lift, and it can also change the load distribution on the wing through deflection. For this reason, we adopted a passive flap structure for the load reduction and investigated its effectiveness by an analytical method based on the blade element moment theory. Flap torsional stiffness required for the design of the passive flap can be obtained by calculating the flap moment based on the analytic method. Comparison between a flapped and a fixed blade showed the effect of the flap on load reduction in a high amplitude wave condition. [ABSTRACT FROM AUTHOR]

The evolution of turbulence characteristics downstream of a laboratory-scale three-bladed horizontal axis turbine is investigated in this study. Large eddy simulation (LES) coupled with the Actuator Line Modelling (ALM) is used to simulate the flow. The numerical results compare well against experimental data, which shows that the LES/ALM technique is a powerful tool for simulating tidal stream turbines. The present study aims to obtain a better understanding of the turbulence characteristics of flow in the turbine wake by removing deterministic velocity fluctuations stemmed from the turbine rotation. Large eddy simulation is able to provide high-resolution spatial and temporal information needed for this work. The filtering process helps to have a clearer view of the flow structures downstream by tracking the streamwise variations of turbulence intensity and turbulent kinetic energy and, reveals a transition zone started shortly behind the turbine with a peak in the turbulence intensity. This study introduces turbulence intensity and turbulent kinetic energy as quantitative criteria to split the turbine wake into distinct regions. This research shows that to investigate and explain the influence of different upstream and operation conditions on the flow characteristics in the turbine wake, a well understanding of flow characteristic changes in the transition zone is necessary. • Flow around a laboratory-scale tidal stream turbine is simulated numerically. • Actuator Line Method (ALM) was combined with a Large Eddy Simulation (LES) solver. • Verifying the results with comparing to detailed measurements. • Filtering out deterministic velocity fluctuations stemmed from the turbine rotation. • Revealing 3 distinct zones for the turbulence characteristics behind a tidal turbine. [ABSTRACT FROM AUTHOR]

This study presents results from laboratory experiments to investigate the wake structure in the lee side of a scaled three-bladed horizontal axis tidal stream turbine with a mono-pile support structure. Experiments are conducted for a range of approaching flow velocity and installation height of rotor. Analysis of the results shows that bed shear stress increases with the increase of approaching velocity and decrease of installation height within 2 D (D is the diameter of the rotor) downstream of the rotor. The flow field within 2 D downstream of the rotor is greatly influenced by the presence of nacelle and mono-pile. Low stream-wise flow velocity and large turbulence intensity level is detected along the flume center right behind the nacelle and mono-pile from 1 D to 2 D downstream of the rotor. Stream-wise velocity at the blade tip height lower than the nacelle increases sharply from 1 D to 2 D and gradually grows afterwards. Correspondingly, the turbulence intensity decreases quickly from 1 D to 2 D and slowly afterwards. Large bed shear stress is measured from 1 D to 2 D , which is closely related to turbulence induced by the mono-pile. It is also found that the presence of the mono-pile might make the flow field more 'disc-shaped'. • Bed shear stress is greatly affected by the presence of the mono pile.. • Velocity recovers quickly within two diameter downstream and slowly afterwards. • Turbulence intensity declines significantly within two diameter downstream and gradually afterwards. • The mono pile might make the turbulence field more 'disc-shaped'. [ABSTRACT FROM AUTHOR]

Tidal stream turbines may suffer severe scour in the marine environment, which poses a threat to their structural stability. However, there has been limited research conducted on the scour processes around tidal stream turbines. In order to address this gap, physical experiments are conducted to investigated scour development around a tripod-supported tidal stream turbine. The experimental results reveal that the scour pattern around the turbine model is greatly influenced by the alignment angle, as it affects the interaction between the incoming flow and the tripod foundation. Substantial scour holes are formed on the lateral sides downstream of the turbine model, indicating highly turbulent flow in this region. Furthermore, under simulated tidal current conditions, fluctuations in the temporal scour depth are observed due to the reversing flow direction and the migration of ripples. Additionally, it is found that the flow velocity exhibits a linear relationship with the scour depth, regardless of the flow conditions. Taking into consideration the influence of the tripod foundation and the turbine rotor, a prediction equation based on the effective flow work is proposed to estimate the final scour depth of the turbine model. The equation is applicable to both the steady and simulated tidal current conditions. • Scour characteristics around the tripod foundation of a tidal stream turbine are presented. • The temporal scour depth development is examined, considering the effects from flow intensities and alignment angles. • An empirical equation based on effective flow work is proposed to predict scour depth of a tidal stream turbine. [ABSTRACT FROM AUTHOR]

This study evaluates correction methods for the actuator line method in tidal stream turbine calculations. Findings indicate that three-dimensional Gaussian distribution coefficients align closely with experimental results when ε = 2dr. Tip loss correction addresses abnormal axial force coefficient elevation at the blade tip, while stall delay correction minimally impacts standard turbine operation. Root loss correction slightly affects the root vortex but notably delays the disappearance of the nacelle after tail flow's bimodal region to 4D, contrary to observations. Using a cylinder correction at the blade root improves the root vortex representation. Enhanced ALM, combined with LES, simulates wake and energy loss across varying turbulence intensities. At low turbulence, the spiral vortex structure is clearer, with fewer stray vortices and a more regular circular shape. Increasing turbulence blurs the structure, introducing more turbulent vortices and losing regularity. Entropy production concept represents energy losses as total, direct, and turbulence entropy production. Direct entropy production is minimal, localized at blade tip, nacelle, and support structures due to significant velocity gradients. Indirect entropy production causes substantial energy loss, resembling wake flow's vortex pattern due to turbulent pulsation. With higher turbulence, EPR, EPDD, and EPTD decline as wake vortices are disrupted, reducing energy loss. • The actuator line method has been modified with various correction methods to make it more applicable to tidal stream turbines And the results of the new method are in good agreement with that of experiment and blade-resolved method. • Implementing the cylinder correction at the blade's root provides a more accurate representation of the root vortex's shape. • The vortex characteristics of the wake can be well captured with the combination of the LES and the modified ALM. • The energy loss is larger for indirect than direct entropy dissipation, and is distributed at the blade position as well as at the support structure. • With escalating turbulence, EPR decreases due to the destruction of wake vortices by small-scale vortices, leading to reduced energy dissipation. [ABSTRACT FROM AUTHOR]

Tidal stream turbine (TST) is a reliable machine for converting tidal stream energy to electric energy. However, the efficiency of power generation will be severely affected by the increasing marine attachment on TST blades. Accurate identification of attachments is very important for their removal. This paper proposes a semi-supervised video segmentation network (SVSN) to recognize attachments in underwater video sources. To alleviate the labeling burden, only a small number of video frames need manual annotation, and sufficient labeled data are collected by a data augmentation algorithm. For utilizing the remaining video frames, these unlabeled data and the labeled data are used to train the SVSN based on semi-supervised adversarial learning. In this way, these two kinds of data benefit from each other, making the network to learn general features for better generalization ability. The SVSN includes a generator and a discriminator. The generator is a modified SegNet to obtain initial segmentation maps. The discriminator, a simple fully convolutional network, provides pixel-wise confidence maps for the semi-supervised adversarial learning. Besides, it enhances the generator segmentation quality via considering object boundary areas. Experimental results demonstrate that precise attachment recognition and fast uncertainty estimation can be accomplished under harsh submerged conditions. • Sufficient labeled images are acquired by a continuous rotation generation algorithm. • During the training stage, the generator is a modified SegNet. The discriminator provides pixel-wise confidence maps. • The method - a semi-supervised video segmentation network, is used to recognize attachment in underwater video sources. [ABSTRACT FROM AUTHOR]

This paper presents a method for the probabilistic evaluation of the failure rates of mechanical components in a typical power take-off (PTO) system of a horizontal-axis tidal stream turbine (HATT). The method is based on a modification of the method of the influence factors, when base failure rates, relevant influence factors and, subsequently, resulting failure rates are treated as random variables. The prior (i.e., initial) probabilistic distribution of the failure rates of a HATT component is generated using data for similar components from other industries, while taking into account actual characteristics of the component and site-specific operating and environmental conditions of the HATT. A posterior distribution of the failure rate is estimated numerically based on a Bayesian approach as new information about the component performance in an operating HATT becomes available. The posterior distribution is then employed to obtain the updated mean and lower and upper confidence limits of the failure rate. The proposed method is illustrated by applying it to the evaluation of the failure rates of two key components of the PTO system of a typical HATT—main seal and main bearing. In particular, it is shown that uncertainty associated with the method itself has a major influence on the failure rate evaluation. The proposed method is useful for the reliability assessment of both PTO designs of new HATTs and PTO systems of operating HATTs.

There is uncertainty on the ecological effects of tidal stream turbines. Concerns include animal collision with turbine blades, disruption of migratory and foraging behaviour, attraction of animals to prey aggregating around turbines, or conversely displacement of animals from preferred habitat. This study used concurrent ecological and physical measurements to show the predictability of fish school characteristics (presence, school area and height above seabed) in a high energy tidal site across spring/neap, ebb/flood and daily cycles, and how this changed around a turbine structure. The rate of schools and school area per hour increased by 1.74 and 1.75 times respectively around a turbine structure compared to observations under similar conditions without a turbine structure. The largest schools occurred at peak flow speeds and the vertical distribution of schools over the diel cycle was altered around the turbine structure. While predictable attraction or aggregation of prey may increase prey availability and predator foraging efficiency, attraction of predators has the potential to increase animal collision risk. Predictable changes from the installation of turbine structures can be used to estimate cumulative effects on predators at a population level. This study can guide a strategic approach to the monitoring and management of turbines and arrays. • Fish school characteristics (rate, area, height) predictable over tidal & diel cycles. • 1.74 times more schools/hour around a turbine support structure. • Largest schools at peak flow speeds. • 5.66 times more schools/hour downstream of turbine structure at flow speeds <1 m/s. • Vertical distribution of schools over diel cycle changed around turbine structure. [ABSTRACT FROM AUTHOR]

As previously experienced by the wind industry, it is envisaged that tidal stream turbine blades will present misalignments or blade deformations over time as they are constantly working under harsh and highly unsteady environments. Blade misalignment will affect the power capture of a tidal stream turbine and if not detected in time could affect other components of the drive train. Therefore, the aim of this paper is to compare the use of two numerical modelling techniques to predict the performance of a tidal stream turbine working under off-design conditions, in this case, the misalignment of one or more blades. The techniques used in this study are Blade Element Momentum Theory and Computational Fluid Dynamics. The numerical models simulate the performance of a three-bladed horizontal axis tidal stream turbine with one or two blades offset from the optimum pitch setting. The simulations were undertaken at 1.0 m/s flow speeds. The results demonstrated that both unsteady BEMT and steady or transient CFD are able to predict power coefficients when there is a certain level of misalignment in one or even two blades. However, both techniques failed to accurately predict a loss of power performance at high rotational speeds. [ABSTRACT FROM AUTHOR]

Abstract Tidal stream turbines are subject to large hydrodynamic loads, including those induced by extreme waves. Scale model testing in the laboratory plays an important role in ensuring that full scale tidal turbines are designed and operated in a manner that is appropriate for harsh ocean environments where waves and tidal currents coexist. For the first time, a fully-instrumented scaled tidal turbine is tested in short-duration focused wave groups representative of extreme environmental load cases expected at energetic tidal sites. In this paper, the subsequent variations in rotor-based loads, power and blade root bending moments are reported. These measurements are found to strongly follow the spectral and temporal form of the focused wave conditions, and peak loads and power output are found to exceed current-only values by 85% and 200% respectively. These rotor-averaged values display a high level of repeatability, demonstrating the suitability of focused waves for testing seabed-mounted tidal turbines. Extreme blade loads, which are dependent on angular position relative to wave phase, are captured through rapidly obtained repeat tests. New insight is subsequently gained into loading and response of tidal turbines in extreme sea conditions. Highlights • Focused wave groups successfully produced in energetic currents of 0.8 m/s. • Fully-instrumented tidal turbine tested in these extreme wave-current conditions. • Peak loads and power output exceed current-only values by 80% and 200% respectively. • Measured loads follow temporal and spectral form of generated focused waves. [ABSTRACT FROM AUTHOR]