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Keywords = renewable wave energy

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15 pages, 2188 KiB  
Article
Research and Simulation Analysis on a Novel U-Tube Type Dual-Chamber Oscillating Water Column Wave Energy Conversion Device
by Shaohui Yang, Haijian Li, Yan Huang, Jianyu Fan, Zhichang Du, Yongqiang Tu, Chenglong Li and Beichen Lin
Energies 2025, 18(15), 4141; https://doi.org/10.3390/en18154141 - 5 Aug 2025
Abstract
With the development of wave energy, a promising renewable resource, oscillating water column (OWC) devices, has been extensively studied for its potential in harnessing this energy. However, traditional OWC devices face challenges such as corrosion and damage from prolonged exposure to harsh marine [...] Read more.
With the development of wave energy, a promising renewable resource, oscillating water column (OWC) devices, has been extensively studied for its potential in harnessing this energy. However, traditional OWC devices face challenges such as corrosion and damage from prolonged exposure to harsh marine environments, limiting their long-term viability and efficiency. To address these limitations, this paper proposes a novel U-tube type dual chamber OWC wave energy conversion device integrated within a marine vehicle. The research involves the design of a U-tube dual-chamber OWC device, which utilizes the pitch motion of a marine vehicle to drive the oscillation of water columns within the U-tube, generating reciprocating airflow that drives an air turbine. Numerical simulations using computational fluid dynamics (CFD) were conducted to analyze the effects of various structural dimensions, including device length, width, air chamber height, U-tube channel width, and bottom channel height, on the aerodynamic power output. The simulations considered real sea conditions, focusing on low-frequency waves prevalent in China’s sea areas. Simulation results reveal that increasing the device’s length and width substantially boosts aerodynamic power, while air chamber height and U-tube channel width have minor effects. These findings provide valuable insights into the optimal design of U-tube dual-chamber OWC devices for efficient wave energy conversion, laying the foundation for future physical prototype development and experimental validation. Full article
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31 pages, 9769 KiB  
Review
Recent Advances of Hybrid Nanogenerators for Sustainable Ocean Energy Harvesting: Performance, Applications, and Challenges
by Enrique Delgado-Alvarado, Enrique A. Morales-Gonzalez, José Amir Gonzalez-Calderon, Ma. Cristina Irma Peréz-Peréz, Jesús Delgado-Maciel, Mariana G. Peña-Juarez, José Hernandez-Hernandez, Ernesto A. Elvira-Hernandez, Maximo A. Figueroa-Navarro and Agustin L. Herrera-May
Technologies 2025, 13(8), 336; https://doi.org/10.3390/technologies13080336 - 2 Aug 2025
Viewed by 311
Abstract
Ocean energy is an abundant, eco-friendly, and renewable energy resource that is useful for powering sensor networks connected to the maritime Internet of Things (MIoT). These sensor networks can be used to measure different marine environmental parameters that affect ocean infrastructure integrity and [...] Read more.
Ocean energy is an abundant, eco-friendly, and renewable energy resource that is useful for powering sensor networks connected to the maritime Internet of Things (MIoT). These sensor networks can be used to measure different marine environmental parameters that affect ocean infrastructure integrity and harm marine ecosystems. This ocean energy can be harnessed through hybrid nanogenerators that combine triboelectric nanogenerators, electromagnetic generators, piezoelectric nanogenerators, and pyroelectric generators. These nanogenerators have advantages such as high-power density, robust design, easy operating principle, and cost-effective fabrication. However, the performance of these nanogenerators can be affected by the wear of their main components, reduction of wave frequency and amplitude, extreme corrosion, and sea storms. To address these challenges, future research on hybrid nanogenerators must improve their mechanical strength, including materials and packages with anti-corrosion coatings. Herein, we present recent advances in the performance of different hybrid nanogenerators to harvest ocean energy, including various transduction mechanisms. Furthermore, this review reports potential applications of hybrid nanogenerators to power devices in marine infrastructure or serve as self-powered MIoT monitoring sensor networks. This review discusses key challenges that must be addressed to achieve the commercial success of these nanogenerators, regarding design strategies with advanced simulation models or digital twins. Also, these strategies must incorporate new materials that improve the performance, reliability, and integration of future nanogenerator array systems. Thus, optimized hybrid nanogenerators can represent a promising technology for ocean energy harvesting with application in the maritime industry. Full article
(This article belongs to the Special Issue Technological Advances in Science, Medicine, and Engineering 2024)
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19 pages, 18533 KiB  
Article
Modeling of Marine Assembly Logistics for an Offshore Floating Photovoltaic Plant Subject to Weather Dependencies
by Lu-Jan Huang, Simone Mancini and Minne de Jong
J. Mar. Sci. Eng. 2025, 13(8), 1493; https://doi.org/10.3390/jmse13081493 - 2 Aug 2025
Viewed by 96
Abstract
Floating solar technology has gained significant attention as part of the global expansion of renewable energy due to its potential for installation in underutilized water bodies. Several countries, including the Netherlands, have initiated efforts to extend this technology from inland freshwater applications to [...] Read more.
Floating solar technology has gained significant attention as part of the global expansion of renewable energy due to its potential for installation in underutilized water bodies. Several countries, including the Netherlands, have initiated efforts to extend this technology from inland freshwater applications to open offshore environments, particularly within offshore wind farm areas. This development is motivated by the synergistic benefits of increasing site energy density and leveraging the existing offshore grid infrastructure. The deployment of offshore floating photovoltaic (OFPV) systems involves assembling multiple modular units in a marine environment, introducing operational risks that may give rise to safety concerns. To mitigate these risks, weather windows must be considered prior to the task execution to ensure continuity between weather-sensitive activities, which can also lead to additional time delays and increased costs. Consequently, optimizing marine logistics becomes crucial to achieving the cost reductions necessary for making OFPV technology economically viable. This study employs a simulation-based approach to estimate the installation duration of a 5 MWp OFPV plant at a Dutch offshore wind farm site, started in different months and under three distinct risk management scenarios. Based on 20 years of hindcast wave data, the results reveal the impacts of campaign start months and risk management policies on installation duration. Across all the scenarios, the installation duration during the autumn and winter period is 160% longer than the one in the spring and summer period. The average installation durations, based on results from 12 campaign start months, are 70, 80, and 130 days for the three risk management policies analyzed. The result variation highlights the additional time required to mitigate operational risks arising from potential discontinuity between highly interdependent tasks (e.g., offshore platform assembly and mooring). Additionally, it is found that the weather-induced delays are mainly associated with the campaigns of pre-laying anchors and platform and mooring line installation compared with the other campaigns. In conclusion, this study presents a logistics modeling methodology for OFPV systems, demonstrated through a representative case study based on a state-of-the-art truss-type design. The primary contribution lies in providing a framework to quantify the performance of OFPV installation strategies at an early design stage. The findings of this case study further highlight that marine installation logistics are highly sensitive to local marine conditions and the chosen installation strategy, and should be integrated early in the OFPV design process to help reduce the levelized cost of electricity. Full article
(This article belongs to the Special Issue Design, Modeling, and Development of Marine Renewable Energy Devices)
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39 pages, 2898 KiB  
Review
Floating Solar Energy Systems: A Review of Economic Feasibility and Cross-Sector Integration with Marine Renewable Energy, Aquaculture and Hydrogen
by Marius Manolache, Alexandra Ionelia Manolache and Gabriel Andrei
J. Mar. Sci. Eng. 2025, 13(8), 1404; https://doi.org/10.3390/jmse13081404 - 23 Jul 2025
Viewed by 691
Abstract
Excessive reliance on traditional energy sources such as coal, petroleum, and gas leads to a decrease in natural resources and contributes to global warming. Consequently, the adoption of renewable energy sources in power systems is experiencing swift expansion worldwide, especially in offshore areas. [...] Read more.
Excessive reliance on traditional energy sources such as coal, petroleum, and gas leads to a decrease in natural resources and contributes to global warming. Consequently, the adoption of renewable energy sources in power systems is experiencing swift expansion worldwide, especially in offshore areas. Floating solar photovoltaic (FPV) technology is gaining recognition as an innovative renewable energy option, presenting benefits like minimized land requirements, improved cooling effects, and possible collaborations with hydropower. This study aims to assess the levelized cost of electricity (LCOE) associated with floating solar initiatives in offshore and onshore environments. Furthermore, the LCOE is assessed for initiatives that utilize floating solar PV modules within aquaculture farms, as well as for the integration of various renewable energy sources, including wind, wave, and hydropower. The LCOE for FPV technology exhibits considerable variation, ranging from 28.47 EUR/MWh to 1737 EUR/MWh, depending on the technologies utilized within the farm as well as its geographical setting. The implementation of FPV technology in aquaculture farms revealed a notable increase in the LCOE, ranging from 138.74 EUR/MWh to 2306 EUR/MWh. Implementation involving additional renewable energy sources results in a reduction in the LCOE, ranging from 3.6 EUR/MWh to 315.33 EUR/MWh. The integration of floating photovoltaic (FPV) systems into green hydrogen production represents an emerging direction that is relatively little explored but has high potential in reducing costs. The conversion of this energy into hydrogen involves high final costs, with the LCOH ranging from 1.06 EUR/kg to over 26.79 EUR/kg depending on the complexity of the system. Full article
(This article belongs to the Special Issue Development and Utilization of Offshore Renewable Energy)
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18 pages, 1709 KiB  
Article
Fluid and Dynamic Analysis of Space–Time Symmetry in the Galloping Phenomenon
by Jéssica Luana da Silva Santos, Andreia Aoyagui Nascimento and Adailton Silva Borges
Symmetry 2025, 17(7), 1142; https://doi.org/10.3390/sym17071142 - 17 Jul 2025
Viewed by 299
Abstract
Energy generation from renewable sources has increased exponentially worldwide, particularly wind energy, which is converted into electricity through wind turbines. The growing demand for renewable energy has driven the development of horizontal-axis wind turbines with larger dimensions, as the energy captured is proportional [...] Read more.
Energy generation from renewable sources has increased exponentially worldwide, particularly wind energy, which is converted into electricity through wind turbines. The growing demand for renewable energy has driven the development of horizontal-axis wind turbines with larger dimensions, as the energy captured is proportional to the area swept by the rotor blades. In this context, the dynamic loads typically observed in wind turbine towers include vibrations caused by rotating blades at the top of the tower, wind pressure, and earthquakes (less common). In offshore wind farms, wind turbine towers are also subjected to dynamic loads from waves and ocean currents. Vortex-induced vibration can be an undesirable phenomenon, as it may lead to significant adverse effects on wind turbine structures. This study presents a two-dimensional transient model for a rigid body anchored by a torsional spring subjected to a constant velocity flow. We applied a coupling of the Fourier pseudospectral method (FPM) and immersed boundary method (IBM), referred to in this study as IMERSPEC, for a two-dimensional, incompressible, and isothermal flow with constant properties—the FPM to solve the Navier–Stokes equations, and IBM to represent the geometries. Computational simulations, solved at an aspect ratio of ϕ=4.0, were analyzed, considering Reynolds numbers ranging from Re=150 to Re = 1000 when the cylinder is stationary, and Re=250 when the cylinder is in motion. In addition to evaluating vortex shedding and Strouhal number, the study focuses on the characterization of space–time symmetry during the galloping response. The results show a spatial symmetry breaking in the flow patterns, while the oscillatory motion of the rigid body preserves temporal symmetry. The numerical accuracy suggested that the IMERSPEC methodology can effectively solve complex problems. Moreover, the proposed IMERSPEC approach demonstrates notable advantages over conventional techniques, particularly in terms of spectral accuracy, low numerical diffusion, and ease of implementation for moving boundaries. These features make the model especially efficient and suitable for capturing intricate fluid–structure interactions, offering a promising tool for analyzing wind turbine dynamics and other similar systems. Full article
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23 pages, 2079 KiB  
Article
Offshore Energy Island for Sustainable Water Desalination—Case Study of KSA
by Muhnad Almasoudi, Hassan Hemida and Soroosh Sharifi
Sustainability 2025, 17(14), 6498; https://doi.org/10.3390/su17146498 - 16 Jul 2025
Viewed by 447
Abstract
This study identifies the optimal location for an offshore energy island to supply sustainable power to desalination plants along the Red Sea coast. As demand for clean energy in water production grows, integrating renewables into desalination systems becomes increasingly essential. A decision-making framework [...] Read more.
This study identifies the optimal location for an offshore energy island to supply sustainable power to desalination plants along the Red Sea coast. As demand for clean energy in water production grows, integrating renewables into desalination systems becomes increasingly essential. A decision-making framework was developed to assess site feasibility based on renewable energy potential (solar, wind, and wave), marine traffic, site suitability, planned developments, and proximity to desalination facilities. Data was sourced from platforms such as Windguru and RETScreen, and spatial analysis was conducted using Inverse Distance Weighting (IDW) and Multi-Criteria Decision Analysis (MCDA). Results indicate that the central Red Sea region offers the most favorable conditions, combining high renewable resource availability with existing infrastructure. The estimated regional desalination energy demand of 2.1 million kW can be met using available renewable sources. Integrating these sources is expected to reduce local CO2 emissions by up to 43.17% and global desalination-related emissions by 9.5%. Spatial constraints for offshore installations were also identified, with land-based solar energy proposed as a complementary solution. The study underscores the need for further research into wave energy potential in the Red Sea, due to limited real-time data and the absence of a dedicated wave energy atlas. Full article
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24 pages, 10449 KiB  
Article
Quantifying the System Benefits of Ocean Energy in the Context of Variability: A UK Example
by Donald R. Noble, Shona Pennock, Daniel Coles, Timur Delahaye and Henry Jeffrey
Energies 2025, 18(14), 3717; https://doi.org/10.3390/en18143717 - 14 Jul 2025
Viewed by 191
Abstract
Recent studies have shown benefits of using tidal stream and wave energy in the electricity generation mix to improve supply–demand balancing on annual/subannual timeframes. This paper investigates this further by considering the variability of solar photovoltaic, onshore and offshore wind, wave, and tidal [...] Read more.
Recent studies have shown benefits of using tidal stream and wave energy in the electricity generation mix to improve supply–demand balancing on annual/subannual timeframes. This paper investigates this further by considering the variability of solar photovoltaic, onshore and offshore wind, wave, and tidal stream over multiple years. It also considers their ability to match with electricity demand when combined. Variability of demand and generation can have a significant impact on results. Over the sample of five years considered (2015–2019), demand varied by around 3%, and the availability of each renewable technology differed by up to 9%. This highlights the importance of considering multiple years of input data when assessing power system impacts, instead of relying on an ‘average’ year. It is also key that weather related correlations between renewable resources and with demand can be maintained in the data. Results from an economic dispatch model of Great Britain’s power system in 2030 are even more sensitive to the input data year, with costs and carbon emissions varying by up to 21% and 45%, respectively. Using wave or tidal stream as part of the future energy mix was seen to have a positive impact in all cases considered; 1 GW of wave and tidal (0.57% of total capacity) reduces annual dispatch cost by 0.2–1.3% and annual carbon emissions by 2.3–3.5%. These results lead to recommended best practises for modelling high renewable power systems, and will be of interest to modellers and policy makers. Full article
(This article belongs to the Special Issue Policy and Economic Analysis of Energy Systems)
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27 pages, 4005 KiB  
Article
Quantum-Enhanced Predictive Degradation Pathway Optimization for PV Storage Systems: A Hybrid Quantum–Classical Approach for Maximizing Longevity and Efficiency
by Dawei Wang, Shuang Zeng, Liyong Wang, Baoqun Zhang, Cheng Gong, Zhengguo Piao and Fuming Zheng
Energies 2025, 18(14), 3708; https://doi.org/10.3390/en18143708 - 14 Jul 2025
Viewed by 252
Abstract
The increasing deployment of photovoltaic and energy storage systems (ESSs) in modern power grids has highlighted the critical challenge of component degradation, which significantly impacts system efficiency, operational costs, and long-term reliability. Conventional energy dispatch and optimization approaches fail to adequately mitigate the [...] Read more.
The increasing deployment of photovoltaic and energy storage systems (ESSs) in modern power grids has highlighted the critical challenge of component degradation, which significantly impacts system efficiency, operational costs, and long-term reliability. Conventional energy dispatch and optimization approaches fail to adequately mitigate the progressive efficiency loss in PV modules and battery storage, leading to suboptimal performance and reduced system longevity. To address these challenges, this paper proposes a quantum-enhanced degradation pathway optimization framework that dynamically adjusts operational strategies to extend the lifespan of PV storage systems while maintaining high efficiency. By leveraging quantum-assisted Monte Carlo simulations and hybrid quantum–classical optimization, the proposed model evaluates degradation pathways in real time and proactively optimizes energy dispatch to minimize efficiency losses due to aging effects. The framework integrates a quantum-inspired predictive maintenance algorithm, which utilizes probabilistic modeling to forecast degradation states and dynamically adjust charge–discharge cycles in storage systems. Unlike conventional optimization methods, which struggle with the complexity and stochastic nature of degradation mechanisms, the proposed approach capitalizes on quantum parallelism to assess multiple degradation scenarios simultaneously, significantly enhancing computational efficiency. A three-layer hierarchical optimization structure is introduced, ensuring real-time degradation risk assessment, periodic dispatch optimization, and long-term predictive adjustments based on PV and battery aging trends. The framework is tested on a 5 MW PV array coupled with a 2.5 MWh lithium-ion battery system, with real-world degradation models applied to reflect light-induced PV degradation (0.7% annual efficiency loss) and battery state-of-health deterioration (1.2% per 100 cycles). A hybrid quantum–classical computing environment, utilizing D-Wave’s Advantage quantum annealer alongside a classical reinforcement learning-based optimization engine, enables large-scale scenario evaluation and real-time operational adjustments. The simulation results demonstrate that the quantum-enhanced degradation optimization framework significantly reduces efficiency losses, extending the PV module’s lifespan by approximately 2.5 years and reducing battery-degradation-induced wear by 25% compared to conventional methods. The quantum-assisted predictive maintenance model ensures optimal dispatch strategies that balance energy demand with system longevity, preventing excessive degradation while maintaining grid reliability. The findings establish a novel paradigm in degradation-aware energy optimization, showcasing the potential of quantum computing in enhancing the sustainability and resilience of PV storage systems. This research paves the way for the broader integration of quantum-based decision-making in renewable energy infrastructure, enabling scalable, high-performance optimization for future energy systems. Full article
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18 pages, 8267 KiB  
Article
Discontinuous Multilevel Pulse Width Modulation Technique for Grid Voltage Quality Improvement and Inverter Loss Reduction in Photovoltaic Systems
by Juan-Ramon Heredia-Larrubia, Francisco M. Perez-Hidalgo, Antonio Ruiz-Gonzalez and Mario Jesus Meco-Gutierrez
Electronics 2025, 14(13), 2695; https://doi.org/10.3390/electronics14132695 - 3 Jul 2025
Viewed by 237
Abstract
In the last decade, countries have experienced increased solar radiation, leading to an increase in the use of solar photovoltaic (PV) systems to boost renewable energy generation. However, the high solar penetration into these systems can disrupt the normal operation of the distribution [...] Read more.
In the last decade, countries have experienced increased solar radiation, leading to an increase in the use of solar photovoltaic (PV) systems to boost renewable energy generation. However, the high solar penetration into these systems can disrupt the normal operation of the distribution grid. Thus, a major concern is the impact of these units on power quality indices. To improve these units, one approach is to design more efficient power inverters. This study introduces a pulse width modulation (PWM) technique for multilevel power inverters, employing a sine wave as the carrier wave and an amplitude over-modulated triangular wave as the modulator (PSTM-PWM). The proposed technique improves the waveform quality and increases the AC voltage output of the multilevel inverter compared with that from conventional PWM techniques. In addition, it ensures compliance with the EN50160 standard. These improvements are achieved with a lower modulation order than that used in traditional techniques, resulting in reduced losses in multilevel power inverters. The proposed approach is then implemented using a five-level cascaded H-bridge inverter. In addition, a comparative analysis of the efficiency of multilevel power inverters was performed, contrasting classical modulation techniques with the proposed approach for various modulation orders. The results demonstrate a significant improvement in both total harmonic distortion (THD) and power inverter efficiency. Full article
(This article belongs to the Special Issue Advances in Pulsed-Power and High-Power Electronics)
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37 pages, 11435 KiB  
Article
Hybrid Energy-Powered Electrochemical Direct Ocean Capture Model
by James Salvador Niffenegger, Kaitlin Brunik, Todd Deutsch, Michael Lawson and Robert Thresher
Clean Technol. 2025, 7(3), 52; https://doi.org/10.3390/cleantechnol7030052 - 23 Jun 2025
Viewed by 383
Abstract
Offshore synthetic fuel production and marine carbon dioxide removal can be enabled by direct ocean capture, which extracts carbon dioxide from the ocean that then can be used as a feedstock for fuel production or sequestered underground. To maximize carbon capture, plants require [...] Read more.
Offshore synthetic fuel production and marine carbon dioxide removal can be enabled by direct ocean capture, which extracts carbon dioxide from the ocean that then can be used as a feedstock for fuel production or sequestered underground. To maximize carbon capture, plants require a variety of low-carbon energy sources to operate, such as variable renewable energy. However, the impacts of variable power on direct ocean capture have not yet been thoroughly investigated. To facilitate future deployments, a generalizable model for electrodialysis-based direct ocean capture plants is created to evaluate plant performance and electricity costs under intermittent power availability. This open-source Python-based model captures key aspects of the electrochemistry, ocean chemistry, post-processing, and operation scenarios under various conditions. To incorporate realistic energy supply dynamics and cost estimates, the model is coupled with the National Renewable Energy Laboratory’s H2Integrate tool, which simulates hybrid energy system performance profiles and costs. This integrated framework is designed to provide system-level insights while maintaining computational efficiency and flexibility for scenario exploration. Initial evaluations show similar results to those predicted by the industry, and demonstrate how a given plant could function with variable power in different deployment locations, such as with wind energy off the coast of Texas and with wind and wave energy off the coast of Oregon. The results suggest that electrochemical systems with greater tolerances for power variability and low minimum power requirements may offer operational advantages in variable-energy contexts. However, further research is needed to quantify these benefits and evaluate their implications across different deployment scenarios. Full article
(This article belongs to the Topic CO2 Capture and Renewable Energy, 2nd Edition)
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25 pages, 4997 KiB  
Article
Use of Machine-Learning Techniques to Estimate Long-Term Wave Power at a Target Site Where Short-Term Data Are Available
by María José Pérez-Molina and José A. Carta
J. Mar. Sci. Eng. 2025, 13(6), 1194; https://doi.org/10.3390/jmse13061194 - 19 Jun 2025
Viewed by 438
Abstract
Wave energy is a promising renewable resource supporting the decarbonization of energy systems. However, its significant temporal variability necessitates long-term datasets for accurate resource assessment. A common approach to obtaining such data is through climate reanalysis datasets. Nevertheless, reanalysis data may not accurately [...] Read more.
Wave energy is a promising renewable resource supporting the decarbonization of energy systems. However, its significant temporal variability necessitates long-term datasets for accurate resource assessment. A common approach to obtaining such data is through climate reanalysis datasets. Nevertheless, reanalysis data may not accurately capture the local characteristics of wave energy at specific sites. This study proposes a supervised machine-learning (ML) approach to estimate long-term wave energy at locations with only short-term in situ measurements. The method involves training ML models using concurrent short-term buoy data and ERA5 reanalysis data, enabling the extension of wave energy estimates over longer periods using only reanalysis inputs. As a case study, hourly mean significant wave height and energy period data from 2000 to 2023 were analyzed, collected by a deep-water buoy off the coast of Gran Canaria (Canary Islands, Spain). Among the ML techniques evaluated, Multiple Linear Regression (MLR) and Support Vector Regression yielded the most favorable error metrics. MLR was selected due to its lower computational complexity, greater interpretability, and ease of implementation, aligning with the principle of parsimony, particularly in contexts where model transparency is essential. The MLR model achieved a mean absolute error (MAE) of 2.56 kW/m and a root mean square error (RMSE) of 4.49 kW/m, significantly outperforming the direct use of ERA5 data, which resulted in an MAE of 4.38 kW/m and an RMSE of 7.1 kW/m. These findings underscore the effectiveness of the proposed approach in enhancing long-term wave energy estimations using limited in situ data. Full article
(This article belongs to the Special Issue Development and Utilization of Offshore Renewable Energy)
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32 pages, 3308 KiB  
Review
Current Status of Development and Application of Ocean Renewable Energy Technology
by Xing Su, Jinmao Chen, Liqian Yuan, Wanli Xu, Chunhua Xiong and Xudong Wang
Sustainability 2025, 17(12), 5648; https://doi.org/10.3390/su17125648 - 19 Jun 2025
Viewed by 897
Abstract
As society continues to develop, the demand for, and dependence on, energy for production and daily life activities are constantly increasing. Driven by environmental awareness and limited land resource, people have begun to reduce their dependence on fossil fuels and turn to the [...] Read more.
As society continues to develop, the demand for, and dependence on, energy for production and daily life activities are constantly increasing. Driven by environmental awareness and limited land resource, people have begun to reduce their dependence on fossil fuels and turn to the ocean for energy. Oceans contain vast and abundant energy resources, such as waves, tides, temperature differences and salinity gradients, all of which can be used for power generation. These resources are clean, efficient, renewable and inexhaustible, making them reliable “blue energy sources”. In addition, they are also generally not limited by land use areas, meeting the need for sustainable energy development. This article summarizes the technical characteristics of ocean energy, such as wave, tidal curre1nt, tidal, temperature difference and salinity gradient energies, and combs through the technological forms of different ocean energies, respectively. It also summarizes the development status of the ocean energy industry, and analyzes the industrial maturity of wave energy, tidal energy, etc, predicts future ocean energy development trends, and highlights the influence of ocean energy on sustainable development. We hope that this article provides a reference for scholars and institutions that dedicated to the research and development of ocean energy. Full article
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23 pages, 5972 KiB  
Article
Forecasting Significant Wave Height Intervals Along China’s Coast Based on Hybrid Modal Decomposition and CNN-BiLSTM
by Kairong Xie and Tong Zhang
J. Mar. Sci. Eng. 2025, 13(6), 1163; https://doi.org/10.3390/jmse13061163 - 12 Jun 2025
Viewed by 583
Abstract
As a renewable and clean energy source with abundant reserves, the development of wave energy relies on accurate predictions of significant wave height (Hs). The fluctuation of Hs is a non-stationary process influenced by seasonal variations in marine climate conditions, which poses significant [...] Read more.
As a renewable and clean energy source with abundant reserves, the development of wave energy relies on accurate predictions of significant wave height (Hs). The fluctuation of Hs is a non-stationary process influenced by seasonal variations in marine climate conditions, which poses significant challenges for accurate predictions. This study proposes a deep learning method based on buoy datasets collected from four research locations in China’s offshore waters over three years (2021–2023, 3-hourly). The hybrid modal decomposition CEEMDAN-VMD is employed for reducing non-stationarity of the Hs sequence, with peak information incorporated as a data augmentation strategy to enhance the performance of deep learning. A probabilistic deep learning model, QRCNN-BiLSTM, was developed using quantile regression, achieving 12-, 24-, and 36-h interval predictions of Hs based on 12 days of historical data with three input features (Hs and wave velocities only). Furthermore, an optimization algorithm that integrates the proposed innovative enhancement strategies is used to automatically adjust the network parameters, making the model more lightweight. Results demonstrate that under a 0.95 prediction interval nominal confidence (PINC), the prediction interval coverage probability (PICP) reaches 100% for at least 6 days across all datasets, indicating that the developed system exhibits superior performance in short-term wave forecasting. Full article
(This article belongs to the Section Ocean Engineering)
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17 pages, 3208 KiB  
Article
Load Prediction Control Study of a Pitch Control System for Large Offshore Wind Turbines
by Xuewei Wang, Shibo Liu, Jianghui Chen, Xiangdong Kong, Chao Ai and Gexin Chen
Appl. Sci. 2025, 15(12), 6468; https://doi.org/10.3390/app15126468 - 9 Jun 2025
Viewed by 396
Abstract
In recent years, the global demand for renewable energy has been steadily increasing, and offshore wind power generation technology has thus developed rapidly, with the optimization of the performance of the pitch control system, as a key technology to ensure the efficient and [...] Read more.
In recent years, the global demand for renewable energy has been steadily increasing, and offshore wind power generation technology has thus developed rapidly, with the optimization of the performance of the pitch control system, as a key technology to ensure the efficient and safe operation of wind turbines, becoming a research hotspot. Offshore wind turbines face complex environmental changes, particularly regarding the load perturbations caused by wind speed, wind direction, waves, and other factors, which have a significant impact on the stability and accuracy of the pitch control system. In order to reduce the impact of load disturbance on pitch accuracy, this paper proposes a pitch control strategy with load disturbance compensation. Firstly, the relationship between hydraulic cylinder displacement and pitch angle is analyzed; then, the mathematical model comparing hydraulic cylinder displacement, servo motor speed, and external load disturbance force is constructed; the hydraulic cylinder position control strategy with load disturbance compensation is proposed; and finally, the effectiveness of the control strategy is verified through simulations and experiments. Full article
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20 pages, 1978 KiB  
Article
Derivation and Experimental Validation of a Parameterized Nonlinear Froude–Krylov Force Model for Heaving-Point-Absorber Wave Energy Converters
by Houssein Yassin, Tania Demonte Gonzalez, Gordon Parker, Giorgio Bacelli and Carlos Michelen
Energies 2025, 18(11), 2968; https://doi.org/10.3390/en18112968 - 4 Jun 2025
Viewed by 398
Abstract
Wave energy converters (WECs) have gained significant attention as a promising renewable energy source. Optimal control strategies, crucial for maximizing energy extraction, have traditionally relied on linear models based on small motion assumptions. However, recent studies indicate that these models do not adequately [...] Read more.
Wave energy converters (WECs) have gained significant attention as a promising renewable energy source. Optimal control strategies, crucial for maximizing energy extraction, have traditionally relied on linear models based on small motion assumptions. However, recent studies indicate that these models do not adequately capture the complex dynamics of WECs, especially when large motions are introduced to enhance power absorption. The nonlinear Froude–Krylov (FK) forces, particularly in heaving-point-absorbers with varying cross-sectional areas, are acknowledged as key contributors to this discrepancy. While high-fidelity computational models are accurate, they are impractical for real-time control applications due to their complexity. This paper presents a parameterized approach for expressing nonlinear FK forces across a wide range of point-absorber buoy shapes inspired by implementing real-time, model-based control laws. The model was validated using measured force data for a stationary spherical buoy subjected to regular waves. The FK model was also compared to a closed-form buoyancy model, demonstrating a significant improvement, particularly with high-frequency waves. Incorporating a scattering model further enhanced force prediction, reducing error across the tested conditions. The outcomes of this work contribute to a more comprehensive understanding of FK forces across a broader range of buoy configurations, simplifying the calculation of the excitation force by adopting a parameterized algebraic model and extending this model to accommodate irregular wave conditions. Full article
(This article belongs to the Special Issue Wave Energy: Theory, Methods, and Applications)
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