The paper proposes a novel five-bucket jacket foundation (FBJF) along with a comprehensive methodology for its prefabrication and transportation. This type of foundation is designed for the installation of wind turbines with capacities exceeding 14 MW in water depths ranging from 30 to 60 m. The paper provides a detailed description of the foundation's offshore prefabrication and semi-wet towing transport. A series of physical model tests were conducted to verify the foundation's self-floating and towing stability of the semi-wet combined system. The test results indicate that the five-bucket jacket foundation possesses stable self-floating capabilities and can be manufactured using a prefabricated platform. With the assistance of the U and K shaped assembled platform (UK platform), the maximum pitch response of the foundation with a 5-m draft can be reduced by more than 75.56 %. Utilizing the UK platform for semi-wet towing will decrease dependence on heavy-lift vessels typically associated with traditional jacket foundation dry-towing and installations in deep water, thereby reducing waiting time and overall costs in installation.

PurposeSluice gate jamming in moving water frequently occurs in hydraulic engineering, while feasible solutions for the gate closure have not been proposed. This paper aims to reveal the main reason for the gate jamming in free discharge and propose feasible solutions for the gate closure.Design/methodology/approachComputational fluid dynamics (CFD) technique was used to obtain the pressure and fluid distributions of a sluice gate in the closing process located in a spillway tunnel. The description of the flow domain, computational mesh model, requirements on setting appropriate boundary conditions and the methodology in describing hydraulic forces were discussed. The reason for the gate jamming was investigated by using the CFD method and verified by model tests.FindingsThe computed results agree well with the experimental results. The results show that the insufficiency of water column force and the excessive friction coefficient are two main reasons for the gate jamming in free discharge.Research limitations/implicationsThe calculation and test errors are inevitable. It is difficult to identify the convective and diffusive transports of vortices in model test in a small gate opening. In that case, precision instruments could be used in the next work to measure the streamline distribution, which will be helpful for the revelation of a jamming gate.Practical implicationsThis paper presents a fast and accurate way to predict the sluice gate jamming in applications, which will be helpful for the systematical solutions of similar problems and the design of a new sluice gate.Originality/valueA simplified model of sluice gate jamming in free discharge is established. The reason for gate jamming in free discharge is clarified, and feasible solutions for gate closure are proposed considering the flow condition and gate geometry.

Strong variability in offshore wind and solar resources compromises energy supply stability. Hybrid offshore wind and solar energy system reduces energy variability and enhances climate resilience, but the persistent knowledge gap in how to configuration constitutes a critical barrier to the stable development of global offshore wind-solar energy. Here, 10 downscaled global climate models are ensembled to resolve the complementarity and optimal configuration of wind and solar energy in offshore hybrid energy systems under climate change. Pronounced complementarity is found between offshore wind and solar energy, and it is projected to exhibit a further upward trend under climate change. And this trend demonstrates pronounced spatial heterogeneity, with high-latitude regions exhibiting significantly stronger synergistic characteristics compared to low-latitude zones. Hybrid systems significantly decrease energy variability, requiring higher offshore solar energy ratio at low-mid latitudes and greater offshore wind energy ratio at high latitudes. After optimization, compared to standalone offshore wind, the average coefficient of variation (CV) of offshore wind-solar hybrid power systems decreases by 1.4, and the optimal average power generation density exceeds 6.6 MW/km2. Under climate change, increasing the ratio of offshore wind energy in high-latitude regions and reducing it in low-latitude regions helps mitigate energy fluctuations under climate change. The results support climate-resilient co-development of offshore wind and solar resources in different regions under climate change.

Hexagonal prism welded joints offer several advantages, including ease of construction, low requirements for processing precision, and suitability for prefabricated installation. These joints have been utilized in the prestressed floating island. Compressive loading represents a common force condition for hexagonal prism welded joints. The current study examines the compressive properties of hexagonal prism welded joints by conducting tests. Four scaled specimens were designed. The study shows that the side length of the rectangular plates and the spacing between the triangular plates affect the force transfer path and load distribution in the hexagonal prism welded joints. These factors have impacted the bearing capacity of hexagonal prism welded joints. These factors have affected the bearing capacity of hexagonal prism welded joints. The corresponding design recommendations are given. Geometric parameter analysis was conducted with validated finite element models. The effects of geometric parameters, like the ratio of side length to thickness of the triangular plate, the ratio of spacing between triangular plates to chord diameter, and the ratio of thickness of the rectangular plate to that of the triangular plate, on bearing capacity were analyzed. From the analysis, it's clear that the buckling reduction factor for the triangular plates was properly fitted. The top rectangular plates in orthogonal directions have their load distribution coefficients determined by the generalized strip deflection method. A theoretical method for calculating the compressive bearing capacity of hexagonal prism welded joints has been developed. The theoretical calculations align closely with the finite element results.

Conventional mooring tension monitoring methods rely on contact sensors, which are expensive and prone to corrosion-induced failure, compromising their stability and durability for long-term monitoring. To address these limitations, this study proposes a stereo-vision-based mooring tension monitoring method for offshore floating photovoltaic (OFPV) platforms. Stereo cameras are used to capture video and identify markers mounted on the platform, from which 3D coordinates are reconstructed. The platform’s motion is then calculated to determine the spatial positions of the fairleads. Based on these positions and the known coordinates of the anchors, mooring tensions can be calculated using a quasi-static approach. A scaled physical model for the actual OFPV platform was produced, and hydrodynamic experiments on the scaled model were conducted to evaluate the performance of the proposed method. The two-chain mooring experiment confirmed the feasibility of this method, and the monitoring accuracies for fairlead position and mooring tension were approximately 97% and 95%, respectively. Moreover, the effects of camera viewing angles and perspective distortion on measurement accuracy were also examined. Based on the four-chain mooring experiment, the stability of this method was validated by successfully enabling simultaneous tension monitoring for multiple mooring lines. Experiment results indicate that the measurement accuracy exceeds 95% and 88% under moderate and extreme conditions, respectively. Compared to conventional methods, this method significantly reduces the measurement cost and implementation difficulty, and shows broad application prospects in both model testing and prototype monitoring.

High-frequency pressure pulsations in pumped storage power station (PSPS) can induce structural vibrations of headrace tunnels, which may cause vibration and noise in nearby residential and heritage areas. This study established a coupled fluid-pipe-surrounding rock coupling (FPSC) model to investigate the propagation and attenuation characteristics of the high-frequency vibration (HFV). A decoupling strategy between fluid and pipe is developed, with the influence of pipe described via scaling factor and phase lag. The governing equations of fluid are discretized using the Finite Difference Method (FDM), forming a time-domain approach for analyzing steady-state hydraulic excitations. Additionally, a finite-infinite element model is established to evaluate vibration response under traveling and standing wave excitations. Results reveal that steady pressure oscillations in the headrace tunnel exhibit periodic spatial distributions, which possesses the characteristic of standing waves, while traveling-wave-induced amplitudes align with the mean trend of the standing wave pattern. The peak vibration amplitude of the pipe wall under standing wave excitation exceeds that under traveling wave excitation by more than 30%. It is essential to evaluate the structural response under multiple reflections and superimposition of the pressure wave inside the headrace tunnel.

Good knowledge of offshore renewable resources is crucial for formulating appropriate energy strategies. However, it remains unclear how China's offshore wind and solar energy will respond to changing climate. Therefore, this study evaluates the effect of climate change on the potential, variability and complementarity of offshore wind and solar resources in China seas in the near future (2031-2060) and far future (2071-2100). The results show that the potential of China's offshore wind and solar resources is generally on a downward trend in the 21st century. Differences in wind and solar potential variation are observed at seasonal scales. During near-future summers, the central South China Sea region is expected to experience increased wind power density but decreased solar power density. Energy stability and complementarity will decrease over the two future periods. In addition, power generation in coastal provinces is calculated. The average annual combined power output in Guangdong province in the near future is 132.8 TWh, which can reduce carbon dioxide emissions by around 58.5 million tons. These findings enhance the understanding of the extent to which China's offshore wind and solar resources can be exploited, in support of long-term climate change mitigation commitments.

Global wind and solar energy potential is vast, but their variability challenges grid stability. While regional assessments about wind and solar energy exist, global systematic evaluations on their stable development potential under climate change remain limited, especially regarding whether joint development across adjacent regions can mitigate their output volatility. This study integrates eight CMIP6 climate models to evaluate historical and future wind and solar energy supply stability for individual and hybrid systems, and explores volatility reduction via adjacent regional joint development. Results show significant, yet declining, global wind and solar energy potential with regional differences. Wind energy exhibits poor stability, with an average coefficient of variation (CV) above 1.2. Notably, wind-solar hybridization greatly enhances stability, reducing the CV to below 0.4. The results further demonstrate prominent advantages of adjacent regional joint utilization for mitigating wind and solar volatility. The average CV of wind energy density in all joint regions declines by over 0.2 with such joint development. Although solar and hybrid systems benefit less from geographical pooling, their variability also decreases. This study clarifies the regional potential of wind and solar energy for stable deployment worldwide under climate change and offers references for regional joint development.

Offshore floating photovoltaic (OFPV) platforms are commonly deployed in nearshore shallow-water regions, where extreme sea states can sharply increase peak mooring tension and fatigue damage. To enhance system reliability, this study proposes a mooring load-reduction method using the additional axial compliance of a helical compression spring. First, a quasi-static spring–catenary model elucidates the load-reduction mechanism through displacement–tension and work analyses. Then, wave-basin experiments are conducted using a 1:25-scale OFPV platform model, with linear springs of six stiffnesses installed in the mooring lines to evaluate their effects on peak tension, platform motion, and fatigue damage. The results show that installing springs significantly reduces the peak tension, with greater effectiveness at higher wave heights. For waves with a 7.0-m maximum height and a 9.0-s peak period in 11.7-m-deep water, the maximum tension decreases from 232.68 kN to 63.13 kN, corresponding to reductions of 72.87% in peak tension and 88.95% in equivalent annual fatigue damage. Meanwhile, the selected prototype compression spring satisfies stiffness, deformation, and fatigue safety requirements. The motion-response results indicate that spring installation mainly increases the horizontal offset, while the vertical displacement and pitch change only slightly. These findings support compliant mooring design for shallow-water OFPV and similar platforms.

The rapid expansion of offshore floating photovoltaic (OFPV) systems, a promising pathway for large-scale solar energy utilization, is critically dependent on understanding platform dynamics under harsh marine conditions. Accurate six-degree-of-freedom (6-DOF) motion measurement is essential for optimizing structural design, ensuring operational safety, and maximizing energy yield. However, existing monitoring techniques are often limited by high cost and inadequate environmental adaptability, restricting their practical application. To address these challenges, this study proposes a novel vision-based 6-DOF measurement system featuring a customized circular target and a hybrid localization framework that integrates deep learning with digital image processing. Target detection is performed using a scene-adaptive YOLOv5 model, while sub-pixel localization is achieved via adaptive ellipse fitting, supplemented by a detection box center fallback strategy to enhance robustness. The 6-DOF motion of the platform is reconstructed through stereo triangulation and rigid-body kinematics. Extensive laboratory experiments, including static accuracy tests, dynamic comparisons with an OptiTrack motion capture system, and hydrodynamic tests on a scaled OFPV platform model, demonstrate the system's accuracy and dynamic feature capture capabilities. Crucially, the system maintains reliable performance under challenging yet realistic ocean simulation scenarios, including complex wave actions and extremely low illumination (5 lx). This study provides a promising and cost-effective technical approach and experimental validation for 6-DOF monitoring of the OFPV platform.

Hydropower plants cascaded by regulating reservoirs (HPCR) are effective for utilizing ultra-high head hydropower resources. The operation of an HPCR requires precise discharge coordination between upstream and downstream plants to maintain system stability and prevent fluctuations in reservoirs levels, which could otherwise disrupt the consistent output of the turbines. In this context, the present study proposes a coordinated control strategy to manage load variations while ensuring discharge coordination. This strategy addresses both scheduled load adjustments and unscheduled small load disturbances. For scheduled load adjustments from the power grid, this study presents a load distribution strategy that allocates the total load across all units in the HPCR, providing the target guide vane opening degree that ensures discharge coordination. For unscheduled small load disturbances, state-space models were developed to represent the HPCR’s behavior under isolated and interconnected operations. The stability and dynamic response were analyzed. Additionally, a novel proportional-integral-derivative (PID) governor control strategy was introduced that incorporated discharge deviation between upstream and downstream plants. Simulation results demonstrate that, under scheduled load adjustment conditions, the proposed method reduces discharge deviation by approximately 3.8% of the rated flow compared with the conventional proportional distribution mode. Furthermore, under unscheduled small load disturbances, the attenuation ratio of oscillations is reduced by up to 15.1%, indicating significantly enhanced damping performance and faster decay of dynamic responses. This approach effectively maintains system stability and regulation quality, enabling the HPCR to achieve rapid and coordinated stabilization in response to unscheduled small load disturbances.

The increasing penetration of renewable energy sources has introduced significant challenges due to their inherent intermittency and uncertainty. Hybrid renewable energy systems have emerged as an effective solution to enhance power supply reliability and support low-carbon energy development. Although existing studies have investigated capacity planning and optimization scheduling separately, their findings remain scattered across different modeling approaches and algorithmic frameworks, lacking systematic structural reviews and analyses. To address this gap, this paper treats capacity planning and optimization scheduling as two relatively independent yet intrinsically connected research directions and establishes a structured review framework. This review systematically categorizes and compares existing studies on hybrid renewable energy systems based on their optimization models, solution algorithms, system configurations (off-grid and grid-connected), and operational timescales. By analyzing the characteristics of single-objective and multi-objective models and comparing the advantages and limitations of traditional optimization methods, artificial intelligence algorithms, hybrid techniques, and common software tools, this review comprehensively summarizes the research status of hybrid renewable energy system optimization. This paper synthesizes existing research through multi-dimensional analysis, systematically elaborating on the application of optimization techniques in capacity planning, and optimization scheduling, providing a clear and structured perspective for methodological selection and future research trends.

Offshore floating photovoltaic structures are subjected to long-term exposure in complex and harsh marine environments, characterized by multi-factor coupling, hidden failure paths, and high uncertainty, making it difficult for conventional analytical methods to effectively reveal the causes of systemic failures. This study establishes a four-dimensional causality system covering design, construction, environment, and management, and proposes a directed hierarchical causality analysis framework that integrates triangular fuzzy numbers, converting fuzzy data into crisp scores defuzzification, and interpretive structural modeling to decode multi-factor interaction paths. The framework identifies a three-layer damage evolution mechanism through a case study of the offshore floating photovoltaic project independently developed by the author's team in China. The results indicate that management factors serve as the underlying drivers, design and environmental factors act as risk transmitters, while connector defects and extreme loads function as direct manifest causes. Based on these findings, a full life-cycle structural management strategy is proposed. This research provides a systematic theoretical framework and empirical evidence that can enhance risk awareness and inform the design of prevention strategies for offshore floating photovoltaic systems throughout their life-cycle.

Offshore floating photovoltaic (OFPV) farms provide a scalable pathway to low-carbon coastal power, but their performance and availability strongly depend on wave climate. Harsh sea states elevate motions, mooring loads and maintenance demands, which increases life-cycle cost and constrains large-array deployment. Floating breakwater-WEC (FB-WEC) systems can protect OFPV by reducing wave transmission and near-field agitation while harvesting part of the incident wave resource as auxiliary power. This review critically synthesises FB-WEC advances with OFPV as the primary application scenario and focuses on how integrated designs balance protection, power capture and structural loads. It establishes an OFPV-oriented taxonomy for breakwater typologies and attenuation mechanisms, compatible WEC families and integration layouts, and compares performance using consistent metrics (e.g., Kt, capture width ratio and LCOE). It further synthesises multi-objective design and control approaches that jointly address wave attenuation, energy yield, OFPV survivability, techno-economic feasibility and environmental effects under realistic sea states. Key bottlenecks include extreme-condition survivability, long-term reliability and the lack of standardised OFPV-relevant performance and ecological assessment frameworks, alongside emerging directions in advanced materials, intelligent PTO/mooring control, modular architectures and data-driven digital twins. Overall, the review clarifies the state of the art and research gaps and provides guidance for designing next-generation FB-WEC systems that enhance OFPV resilience and support sustainable coastal decarbonisation.

This study investigates the wave-slamming response of floating offshore photovoltaic breakwaters under varying wave conditions through combined physical experiments and numerical simulations. A three-dimensional singlering breakwater model was established, and a coupled fluid-structure-mooring numerical framework was developed in OpenFOAM and validated against experimental data. The waveFoam solver was further extended to enable pressure monitoring at moving observation points during mesh deformation, thereby overcoming the limitation of conventional fixed-point monitoring methods. The effects of wave height and wave period on the slamming response were analyzed. Results indicate that, under irregular waves, the slamming force increases markedly with wave height and is primarily governed by it. For each 1 m increase in wave height, the peak piezometric head increases by about 0.32 m, while the mean value increases by approximately 0.28 m. In contrast, the wave period mainly affects the fluctuation characteristics of the slamming response but has a relatively limited influence on the overall force magnitude. Additional simulations under regular waves show that the variation trend with wave period remains generally consistent with that observed under irregular waves.

Floating photovoltaic (FPV) platforms in offshore environments are subjected to complex wave-induced motions and mooring loads, making rapid and reliable response prediction important for structural safety assessment. This study proposes a multivariate point and interval prediction method for a dual-ring box-type FPV platform by integrating graph neural networks, long short-term memory networks, and Bayesian inference. The floater units, mooring lines, and wave excitation are represented as a heterogeneous graph to incorporate physical connectivity and load-transfer relationships. A GNN-LSTM model is developed to capture spatial coupling and temporal evolution, while Monte Carlo Dropout with variable-adaptive calibration is used to quantify uncertainty and construct prediction intervals. Numerical simulations under 25 irregular-wave conditions are used for evaluation. Results show that GAT performs better than GCN in spatial feature extraction, and the LSTM-first strategy provides the best overall balance between accuracy and efficiency, with R2 reaching 0.992. Compared with standalone GNN and LSTM models, the hybrid model improves prediction accuracy, particularly for peak responses, with a peak-error reduction of up to 95.9%. The calibrated 95% intervals achieve coverage close to the nominal level. Prediction uncertainty increases under large wave heights, short periods, and near-resonance conditions. These findings support safety assessment and intelligent monitoring of offshore FPV platforms under complex sea states.

Accurately predicting ski-jump flood discharge atomization is crucial for designing effective disaster-mitigation measures, particularly because low ambient pressure increases the risk of atomized protection in high-altitude regions. However, owing to the complex effects of low ambient pressure on strongly coupled atomized field sources, it is difficult to fully describe the comprehensive behaviour of such sources theoretically, which limits the further development of random splashing numerical models. In this paper, a refined random splashing numerical model characterized by low ambient pressure is developed based on experimental results and applied to high-altitude earth–rockfill dam projects. Compared with the reference ambient pressure condition (P0 = 101.457 kPa), which corresponds to the same flood discharge flow, a decrease in ambient pressure by 0.1P0 leads to a maximum change rate not exceeding 10 m for the characteristic boundary of the 10 mm/h atomized rain intensity line at the QX Hydropower Station. This observation also applies to both the 40 mm/h and 10 mm/h atomized rain intensity lines at the RM Hydropower Station. For the two groups of flip bucket types designed for the RM Hydropower station, the loads associated with atomized protection are predominantly concentrated on the left bank. The maximum height of the 10 mm/h atomized rain intensity line affected by atomized rain ranges from 0.83 to 0.85 times the maximum dam height of 315 m. The distance between the farthest downstream boundary and the Spillway No. 3 outlet is between 666.80 and 692.40 metres. Since the flip bucket shape variations only slightly affect the atomization zone extent, further optimization is needed. The study can provide valuable methodological and decision-making support for safeguarding against existing and potential impacts within areas affected by flood discharge atomization from high-altitude hydropower stations.

Ensuring the operational safety of offshore wind turbine (OWT) structures during their service period requires accurate identification on the operational modal parameters (OMPs), which are not only a crucial parameter which reflect the structure’s vibration characteristics, but also a key index for evaluating the structural healthy status. However, due to the complex and unpredictable ocean environmental circumstances, the measured signals obtained from the actual OWT structures are frequently accompanied by a huge amount of low-frequency, high-energy noise, which has a significant influence on the identification accuracy of OMPs. Therefore, one called CSVS (CEEMDAN-SSA-VMD-SSI) modal identification process, which combined the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), sparrow search algorithm (SSA), variational modal decomposition (VMD) and stochastic subspace identification (SSI) method, was proposed for identifying modal parameters of OWT structures under operational conditions. It aims to mitigate the influence on the identification accuracy resulted from the low-frequency, high-energy noise and investigates the variations of modal parameters based on measured data. Firstly, the CEEMDAN method and VMD process optimized by the SSA were used to decompose the signal and remove the low-frequency, high-energy noises, and then the SSI method was following applied to identify and extract the OMPs from the measured data. Secondly, the efficiency of the proposed CSVS approach to identify OMPs of one 3.3 MW OWT operating in Yellow sea of China, was confirmed based on the measured vibration displacement signals under various operational conditions by comparing the results identified from the classic method. Finally, the distribution characteristics of the natural modal frequency, impeller rotation frequency (1P) and blade sweeping frequency (3P) were furtherly investigated, and the change regulations of identified OMPs with the operational factors including wind speed and rotational speed were also provided. It is indicated that the CSVS method shows the strong resistance to modal aliasing and effectiveness on noise reduction compared to the traditional methods so that it can accurately identify and distinguish the natural modal frequency, 1P frequency and 3P frequency of the OWT structure. Further, it may provide the essential technical support for identifying the OMPs and evaluating the operational safety of OWT structures.

Current static mechanical load (SML) tests for photovoltaic (PV) modules assume uniformly distributed pressure, whereas the actual wind pressure on module surfaces is strongly non-uniform. This study integrates CFD-based flow-field analysis, dual-zone SML tests, EL and I-V measurements, and a validated finite-element/XFEM model to assess wind-induced microcracking under non-uniform loads. Flow-field simulations indicate that the nonuniformity factor between the two regions on the PV module is 1.76, from which the non-uniform equivalent static load levels are obtained. Compared with uniform loading, non-uniform loading significantly redistributes deflection and strain: front-side loading reduces mid-span deflection by 6.5 %, whereas back-side loading increases deflection and amplifies local strains, revealing intrinsic asymmetry between front and back-side loading. EL and I-V results show that non-uniform loading promotes network-like and diagonal cracks concentrated in the high-load region, while short-term power loss remains below 1 %. The FE-XFEM model reproduces these responses and indicates a 16 % reduction in cell crack-initiation load under non-uniform loading. Parametric analysis shows that reducing lower support spacing can decrease peak module deflection and cell stress by up to 17.3 % and 18.7 %, respectively. These findings highlight the need to incorporate wind-load non-uniformity and support conditions into SML testing and PV module design.