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In marine environments, tidal currents exhibit periodic changes in both direction and velocity. Consequently, tidal turbines often operate under yawed conditions. While conventional horizontal-axis turbines show decreased performance and undergo periodic load fluctuations due to blade rotation when yawed, research on the effects of yaw on ducted turbines has been sparse, leaving the underlying impact mechanisms poorly understood. This paper presents a three-dimensional hydrodynamic model of a ducted turbine, developed using the computational fluid dynamics method and validated through flume experiments. The hydrodynamic characteristics of the ducted turbine when operating under yawed conditions are analyzed using large eddy simulation. The findings indicate that yaw does not alter the optimal rotational speed of the ducted turbine. The turbine performance remains superior to non-yawed conditions up to a yaw angle of approximately 7°, peaking with a 1% improvement at 5°, but deteriorates beyond this point, declining by 1.5% at a yaw angle of 10°. In addition, yaw causes a deflection in the wake of the ducted turbine. This deflection increases with the yaw angle, reaching its maximum at a yaw angle of 10° with an angle of about 3.4°, before diminishing. The duct structure significantly influences this deflection, while rotor rotation has a minimal impact on wake deflection. [ABSTRACT FROM AUTHOR]

Surface sediment samples (n = 92) were collected from Hangzhou Bay to investigate the transport and deposition of polybrominated diphenyl ethers (PBDEs) and to assess the ecological risks in Hangzhou Bay. The concentrations of ∑ 7 PBDEs (sum of BDE-28, 47, 99, 100, 153, 154, 183) and BDE-209 ranged from 3.61 to 91.09 pg g−1 and from non-detectable to 2007.52 pg g−1 (dry weight), respectively. The high values of ∑ 7 PBDEs and BDE-209 were commonly occurred at the northeast of Hangzhou Bay and the Nanhui Spit coast of Shanghai. Compared with the south part of the bay, the dominance of BDE-209 was more prominent and the linear correlations between PBDEs concentrations and TOCs as well as median grain size were more significant in the northern Hangzhou Bay. Hydrodynamic forcing on the transport and deposition of PBDEs is primarily responsible for the discrepancy of this spatial distribution in these two parts. In addition to BDE-209, BDEs-153, 99, 47, and 100 were also the abundant congeners. Three principal components were extracted using principal component analysis (PCA), mainly attributed to human activities, erosion of polluted soils via surface runoff and release from products for PC1, PC2 and PC3, respectively. The calculation results of mass inventories, hazard quotients (HQs) and risk quotients (RQs) indicated that the ecological risk of PBDEs in Hangzhou Bay was low. The multiple effect of hydrodynamic forcing with complicated and large-scope tidal currents made it hard to deposit for organic matters and contaminants in Hangzhou Bay. • BDE-209 was dominant in the north area of Hangzhou Bay. • ∑ 7 PBDEs decreased from coastal areas to the center of Hangzhou Bay. • Hydrodynamic forcing influenced spatial distribution of PBDEs. • Hangzhou Bay is at low risk level at present. • Organic matters and contaminants are hard to deposit in Hangzhou Bay. [ABSTRACT FROM AUTHOR]

Accurate tidal current prediction plays a critical role with increasing utilization of tidal energy. The classical prediction approach of the tidal current velocity adopts the harmonic analysis (HA) method. The performance of the HA approach is not ideal to predict the high frequency components of tidal currents due to the lack of capability processing the non-astronomic factor. Recently, machine learning algorithms have been applied to process the non-astronomic factor in the prediction of tidal current. In this paper, a tidal current velocity prediction considering the effect of the multi-layer current velocity method is proposed. The proposed method adopts three machine learning algorithms to establish the prediction models for comparative investigations, namely long-short term memory (LSTM), back-propagation (BP) neural network, and the Elman regression network. In the case study, the tidal current data collected from the real ocean environment were used to validate the proposed method. The results show that the proposed method combined with the LSTM algorithm had higher accuracy than both the commercial tidal prediction tool (UTide) and the other two algorithms. This paper presents a novel tidal current velocity prediction considering the effect of the multi-layer current velocity method, which improves the accuracy of the power flow prediction and contributes to the research in the field of tidal current velocity prediction and the capture of tidal energy. [ABSTRACT FROM AUTHOR]

Waters surrounding Zhoushan Archipelago have the most abundant tidal current energy in China, which makes it a promising site for tidal farm construction in the future. Before deploying tidal current turbines, the potential environmental impacts on surrounding waters must be evaluated. In this work, we focus on the flow field impact assessment of an assumed tidal farm installed in Zhoushan Putuo-Hulu Channel. First, in order to evaluate the tidal characteristics there, a 2-month ADCP campaign is carried out, and a 3-D hydrodynamic model is established and validated with the in-situ measurements. Additionally, tidal current velocity and water depth as well as flow heading asymmetry information are used to evaluate the tidal stream exploitability within this channel. Second, a tidal farm consisting of 115 turbines is planned and assumed to be deployed throughout this channel. Blade element momentum method is used to numerically characterize the flow-turbine interactions, and then the spatial-temporal flow field variations caused by the assumed tidal farm are evaluated. It can be seen from the results that the peak flow speed reduction produced by the tidal farm could be over 0.5 m/s within the wake zones, while the flow velocity increment along two islands could reach 0.6 m/s. In particular, a flow speed phase shift phenomenon can be observed. Besides, the water level experiences a small overall rise, and the difference compared with the reference is within ± 3.0 cm. Moreover, the seabed shear stress within the wake zones could drop by 65%, while the areas along the two islands might see over 100% increase, indicating the risk of sediment deposition and coastal erosion. [ABSTRACT FROM AUTHOR]

Abstract Tidal current turbine, as an effective technical means to contribute to all around the world achieving targets for reducing greenhouse gas emissions and the production of renewable energy, has obtained great concern. It was established that more than 94 TWh per year could be generated in the developable sea area. Many types of tidal current turbine structures and control methods have been proposed, however, the possible increase in power generation must consider parameters such as reliability, cost, and complexity of the control system. The paper presents a review on configuration and control methods of tidal current turbines. The configuration and control methods of tidal current turbines are classified, described and compared, especially for horizontal axis tidal current turbines. Horizontal axis tidal current turbine is more widely used, due to high energy conversion efficiency. Different configuration and corresponding control methods have their advantages and disadvantages, which affect efficiency, maintenance requirements, and the cost of electricity from tidal current. Highlights • The configuration of the main tidal current turbines is detailed. • The structure of horizontal axis tidal current turbine is described. • The control methods of horizontal axis tidal current turbine are illustrated. [ABSTRACT FROM AUTHOR]

Owing to its high resource predictability and power density, tidal current energy has garnered extensive attention worldwide, from both academia and industry, in the past decade. Currently, China is also accelerating the development of tidal current energy because of the abundant tidal current resources along the country's highly populated southeast coasts. The objective of this development is to meet the increasing power demands for coastal cities, islands, and various maritime applications. The tidal current energy conversion systems in China have undergone rapid technological advancements in the past ten years, particularly after the deployment of several large-sized tidal current turbines. Although several review papers have covered the evolution of tidal current energy converters (TCECs) in China since the 1980s, a comprehensive update of the past decade has not been systematically reported, which might be of significant interest to researchers, developers, and investors worldwide. In this paper, we present the state-of-the-art TCEC technological developments in China in terms of scale, efficiency, reliability, and other innovations. Their technology readiness level and problems are also discussed. It is found that TCEC development in China has been diverging toward two different directions: large-sized turbines for grid connection and small-scale turbines for diverse applications in marine environments. Finally, we present the current challenges and future trends of TCEC advancement in China. • Existing tidal current energy converters in China are reviewed. • Development trend of large-scale equipment and diversified applications is analyzed. • Challenges and suggestions for the tidal current energy technology are summarized. [ABSTRACT FROM AUTHOR]

Accurate and reliable tidal current forecasting plays a key role in application of grid-connected tidal current power generation systems. Hence, a novel tidal current prediction method based on a hybrid machine learning method is proposed in this paper. Compared with previous tidal current prediction method, the proposed tidal current prediction method considers the influence of turbulence on multi-layer tidal velocity difference. A hybrid machine learning method based on hierarchical extreme learning machine(H-ELM) and long short-term memory (LSTM) is adopted to reduce effect of the turbulent flow, which enables to increase the accuracy of the prediction result. The tidal data that collected by using acoustic doppler current profiler (ADCP) in Zhejiang province China is used to validate the effectiveness of the proposed method. The results of the case study show that the proposed method has higher accuracy than results from standard harmonic analysis using UTide (a freely available academic research product). • A novel tidal current prediction model considering the multilayer difference caused by the turbulent flow is proposed. • A hybrid machine learning method is adopted to reduce effect of the turbulent flow and increase the prediction accuracy. • Both H-ELM and LSTM methods are applied in the short-term tidal current velocity prediction. [ABSTRACT FROM AUTHOR]

Tidal current energy has received extensive attention from both academia and industry in the past decade due to its high power density and strong predictability. Besides Europe and the United States, China has also made tremendous efforts in tidal current energy development, as this abundant ocean renewable resource is expected to provide consistent and clean power for highly-populated coastal cities or remote islands. To evaluate the tidal current resource potential in China, both national assessments and regional investigations have been conducted with different methods and resolutions. However, these evaluation results have not been systematically collected, which are poorly informed to researchers, developers, and investors. At the same time, the conducted assessments sometimes show discrepancies, indicating the necessity of analysing data uncertainty and improving data quality. Under the circumstances, this work presents a review of tidal current resource assessment studies in China, and most existing evaluations for tidal current energy hotspots have been included, classified and compared. Particularly, these regions of interest are further categorised with their exploitability, based on not only theoretical energy reserve estimation, but also local conditions of bathymetry, transportation, policy, etc. According to the assessment results, Zhoushan Archipelago has been considered the most suitable area for large-scale tidal current energy development in China, and the waters nearby Chengshan Cape and Qiongzhou Strait are also with great potential. Furthermore, assessment result uncertainties are analysed, and suggestions on scientific research, technology innovation, and business investment are also proposed for future China tidal current energy development. • Existing studies on China tidal current resource assessment are re-viewed. • Comprehensive evaluation on tidal current energy development po-tential for each region is performed. • Resource areas are categorised by their suitablity for large-scale de-velopment. • More research attentions on resource assessment of certain regions are needed. • Tidal current characteristics in China indicate the requirement of technological innovations for future development. [ABSTRACT FROM AUTHOR]