Search Results (672)

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

Hydrogen is a potential key component of a carbon-neutral energy carrier and an input to marine industrial processes. This study examines the consequences of coupled hydrogen release and marine environmental factors during floating photovoltaic hydrogen production (FPHP) system failures. A validated three-dimensional numerical model of FPHP comprehensively characterizes hydrogen leakage dynamics under varied rupture diameters (25, 50, 100 mm), transient release duration, dispersion patterns, and wind intensity effects (0–20 m/s sea-level velocities) on hydrogen–air vapor clouds. FLACS-generated data establish the concentration–dispersion distance relationship, with numerical validation confirming predictive accuracy for hydrogen storage tank failures. The results indicate that the wind velocity and rupture size significantly influence the explosion risk; 100 mm ruptures elevate the explosion risk, producing vapor clouds that are 40–65% larger than 25 mm and 50 mm cases. Meanwhile, increased wind velocities (>10 m/s) accelerate hydrogen dilution, reducing the high-concentration cloud volume by 70–84%. Hydrogen jet orientation governs the spatial overpressure distribution in unconfined spaces, leading to considerable shockwave consequence variability. Photovoltaic modules and inverters of FPHP demonstrate maximum vulnerability to overpressure effects; these key findings can be used in the design of offshore platform safety. This study reveals fundamental accident characteristics for FPHP reliability assessment and provides critical insights for safety reinforcement strategies in maritime hydrogen applications. Full article

As the development of offshore wind energy transforms from coastal to deep-sea regions, designing a cost effective mooring system while ensuring the safety of floating offshore wind turbine (FOWT) remains a critical challenge, especially considering extreme wave environments. This study employs a model coupling computational fluid dynamics (CFD) and finite element method (FEM) to investigate the responses of a parked FOWT platform with its mooring system under rogue wave conditions. Specifically, the mooring dynamics are solved using a local discontinuous Galerkin (LDG) method, which is believed to provide high accuracy. Firstly, rogue wave generation and the coupled CFD-FEM are validated through comparisons with existing experimental and numerical data. Secondly, FOWT platform motions and mooring tensions caused by a rogue wave are obtained through simulations, which are compared with the ones caused by a similar peak-clipped rogue wave. Lastly, analysis of four different mooring design schemes is conducted to evaluate their performance on reducing the mooring tensions. The results indicate that the rogue wave leads to significantly enlarged FOWT platform motions and mooring tensions, while doubling the number of mooring lines with specific line angles provides the most balanced performance considering cost-effectiveness and structural safety under identical rogue wave conditions. Full article

Floating offshore wind turbines (FOWTs) unlock superior wind resources and reduce operational barriers. The dynamics of FOWT platforms present added engineering challenges and opportunities. While the motion of the floating platform due to wind and wave disturbances can worsen power quality and increase structural loading, certain movements of the floating platform can be exploited to improve power capture. Consequently, active FOWT platform control methods using conventional and innovative actuation systems are under investigation. This paper develops a novel framework to design nonlinear control laws for six degrees-of-freedom platform motion. The framework uses simplified rigid-body analytical models of the FOWT. Lyapunov’s direct method is used to develop actuator-agnostic unconstrained control laws for platform translational and rotational control. A model based on the NREL-5MW reference turbine on the OC3-Hywind spar-buoy platform is utilized to test the control framework for an ideal actuation scenario. Possible applications using traditional and novel turbine actuators and future research directions are presented. Full article

This study explores virtual sensing techniques for the Eolink floating offshore wind turbine (FOWT), which features a pyramidal platform and a single-point mooring system that enables weathervaning to maximize power production and reduce structural loads. To address the challenges and costs associated with monitoring submerged components, virtual sensors are investigated as an alternative to physical instrumentation. The main objective is to design a virtual sensor of mooring hawser loads using a reduced set of input features from GPS, anemometer, and inertial measurement unit (IMU) data. A virtual sensor is also proposed to estimate the bending moment at the joint of the pyramid masts. The FOWT is modeled in OrcaFlex, and a range of load cases is simulated for training and testing. Under defined sensor sampling conditions, both supervised and physics-informed machine learning algorithms are evaluated. The models are tested under aligned and misaligned environmental conditions, as well as across operating regimes below- and above-rated conditions. Results show that mooring tensions can be estimated with high accuracy, while bending moment predictions also perform well, though with lower precision. These findings support the use of virtual sensing to reduce instrumentation requirements in critical areas of the floating wind platform. Full article

This review provides the recent advancements in nonlinear sea ice modeling for hydroelastic analysis of ice-covered channels and their interaction with floating structures. It surveys theoretical, experimental, and numerical methodologies used to analyze complex coupled sea ice–structure interactions. The paper discusses governing fluid domain solutions, fluid–ice interaction mechanisms, and ice–structure (ship) contact models, alongside experimental techniques and various numerical models. While significant progress has been made, particularly with coupled approaches validated by experimental data, challenges remain in full-scale validation and accurately representing ice properties and dynamic interactions. Findings highlight the increasing importance of understanding sea ice interactions, particularly in the context of climate change, Arctic transportation, and the development of very large floating structures. This review serves as a crucial resource for advancing safe and sustainable Arctic and offshore engineering. Full article

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 study provides a comprehensive overview of vertical-axis wind turbines (VAWTs) for emerging energy applications by combining a bibliometric analysis and a thematic mini-review. Scopus-indexed publications from 1979 to 2025 were analyzed using PRISMA guidelines and bibliometric tools (Bibliometrix, CiteSpace, and VOSviewer) to map global research trends, and a parallel mini-review distilled recent advances into five thematic areas: aerodynamic strategies, advanced materials, urban integration, hybrid systems, and floating offshore platforms. The results reveal that VAWT research output has surged since 2006, led by China with strong contributions from Europe and North America, and is concentrated in leading renewable energy journals. Dominant topics include computational fluid dynamics (CFD) simulations, performance optimization, wind–solar hybrid integration, and adaptation to turbulent urban environments. Technologically, active and passive aerodynamic innovations have boosted performance albeit with added complexity, remaining mostly at moderate technology readiness (TRL 3–5), while advanced composite materials are improving durability and fatigue life. Emerging applications in microgrids, building-integrated systems, and offshore floating platforms leverage VAWTs’ omnidirectional, low-noise operation, although challenges persist in scaling up, control integration, and long-term field validation. Overall, VAWTs are gaining relevance as a complement to conventional turbines in the sustainable energy transition, and this study’s integrated approach identifies critical gaps and high-priority research directions to accelerate VAWT development and help transition these turbines from niche prototypes to mainstream renewable solutions. Full article

This paper presents a method to model and optimize the supply chain processes for floating offshore wind turbines using a network model based on Generalized Multi-Commodity Network Flows (GMCNF). The proposed method represents production bases, base ports, installation sites, component transfer areas, and transportation routes as nodes and arcs within the network. The installation process is modeled using three transport concepts: assembling components at the base port, direct assembly and installation at the installation site, and transferring components to the installation vessel at a nearby port. These processes are expressed as a linear network model, with the objective function set to minimize total transportation and assembly costs. The optimal transportation network is derived by solving the network problem while incorporating constraints such as supply, demand, and transportation capacity. Case studies demonstrate the method’s effectiveness in optimizing the supply chain and evaluating potential new production site locations for floating foundations, considering overall supply chain optimization. Full article

A standard approach to design begins with scaling up state-of-the-art machines to new target dimensions, moving towards larger rotors with lower specific energy to maximize revenue and enable power production in lower wind speed areas. This trend is particularly crucial in floating offshore wind in the Mediterranean Sea, where the high levelized cost of energy poses significant risks to the sustainability of investments in new projects. In this context, the conventional approach of scaling up machines designed for fixed foundations and strong offshore winds may not be optimal. Additionally, modern large-scale wind turbines for offshore applications face challenges in achieving high aerodynamic performance in thick root regions. This study proposes a holistic optimization framework that combines multi-fidelity analyses and tools to address the new challenges in wind turbine rotor design, accounting for the novel demands of this application. The method is based on a modular optimization framework for the aerodynamic design of a new wind turbine rotor, where the cost function block is defined with the aid of a model reduction strategy. The link between the full-order model required to evaluate the target rotor’s performance, the physical aspects of blade aerodynamics, and the optimization algorithm that needs several evaluations of the cost function is provided by the definition of a surrogate model (SM). An intelligent SM definition strategy is adopted to minimize the computational effort required to build a reliable model of the cost function. The strategy is based on the construction of a self-adaptive, automatic refinement of the training space, while the particular SM is defined by the use of stochastic radial basis functions. The goal of this paper is to describe the new aerodynamic design strategy, its performance, and results, presenting a case study of a 15 MW wind turbine blades optimized for specific deepwater sites in the Mediterranean Sea. Full article

Steel lazy wave risers (SLWRs) are critical in offshore hydrocarbon transport for linking subsea wells to floating production facilities in deep-water environments. The incorporation of buoyancy modules reduces curvature-induced stress concentrations in the touchdown zone (TDZ); however, extended operational exposure under cyclic environmental and operational loads results in repeated seabed contact. This repeated interaction modifies the seabed soil over time, gradually forming a trench and altering the riser configuration, which significantly impacts stress patterns and contributes to fatigue degradation. Accurately reconstructing the riser’s evolving profile in the TDZ is essential for reliable fatigue life estimation and structural integrity evaluation. This study proposes a simulation-based framework for the autonomous tracking of SLWRs using a fin-actuated autonomous underwater vehicle (AUV) equipped with a monocular camera and multibeam echosounder. By fusing visual and acoustic data, the system continuously estimates the AUV’s relative position concerning the riser. A dedicated image processing pipeline, comprising bilateral filtering, edge detection, Hough transform, and K-means clustering, facilitates the extraction of the riser’s centerline and measures its displacement from nearby objects and seabed variations. The framework was developed and validated in the underwater unmanned vehicle (UUV) Simulator, a high-fidelity underwater robotics and pipeline inspection environment. Simulated scenarios included the riser’s dynamic lateral and vertical oscillations, in which the system demonstrated robust performance in capturing complex three-dimensional trajectories. The resulting riser profiles can be integrated into numerical models incorporating riser–soil interaction and non-linear hysteretic behavior, ultimately enhancing fatigue prediction accuracy and informing long-term infrastructure maintenance strategies. Full article

Drag embedment anchors (DEAs) provide reliable and cost-effective mooring solutions for floating structures, e.g., platforms, ships, offshore wind turbines, etc., in offshore engineering. Structural stability and operational safety require accurate predictions of their penetration depths and holding capacities across various seabed conditions. In this study, explicit linear regression (LR) models were developed for the first time to predict the penetration depth and holding capacity of DEAs on clay and sand seabed. Buckingham’s theorem was also applied to identify dimensionless groups of parameters that influence DEA behavior, e.g., the penetration depth and holding capacity of the DEAs. LR models were developed and validated against experimental data from the literature for both clay and sand seabed. To evaluate model performance and identify the most accurate LR models to predict DEA behavior, comprehensive sensitivity, error, and uncertainty analyses were performed. Additionally, LR analysis revealed the most influential input parameters impacting penetration depth and holding capacity. Regarding offshore mooring design and geotechnical engineering applications, the proposed LR models offered a practical and efficient approach to estimating DEA performance across various seabed conditions. Full article

In an effort to restrict further increases in climate change, governments and companies are exploring ways to reduce greenhouse gas (GHG) emissions. In this context, the oil industry, which contributes to indirect GHG emissions, is seeking ways to develop solutions to this issue. One such approach focuses on the connection of offshore oil production platforms to the onshore power grid via high-voltage direct current (HVDC), enabling a total or partial reduction in the number of local generators, which are generally powered by gas turbines. Therefore, this work aims to determine the technical feasibility, based on transient and dynamic stability analyses, of electrifying a system composed of six floating production storage and offloading (FPSO) units connected to a hub, which is powered by the onshore grid through submarine cables using HVDC technology. The analysis includes significant contingencies that could lead the system to undesirable operating conditions, allowing for the identification of appropriate remedial control actions. The analysis, based on real data and parameters, was carried out using PSCAD software. The results show that the modeled system is technically viable and could be adopted by oil companies. In addition to aligning with global warming mitigation goals, the proposal includes a complex system modeling approach, with the aim of enabling further study. Full article

This study presents a novel approach in the field of renewable energy, focusing on the power generation capabilities of floating offshore wind turbines (FOWTs). The study addresses the challenges of designing and assessing the power generation of FOWTs due to their multidisciplinary nature involving aerodynamics, hydrodynamics, structural dynamics, and control systems. A hybrid deep learning model combining Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks is proposed to predict the performance of FOWTs accurately and more efficiently than traditional numerical models. This model addresses computational complexity and lengthy processing times of conventional models, offering adaptability, scalability, and efficient handling of nonlinear dynamics. The results for predicting the generator power of a spar-type floating offshore wind turbine (FOWT) in a multivariable parallel time-series dataset using the Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) model showed promising outcomes, offering valuable insights into the model’s performance and potential applications. Its ability to capture a comprehensive range of load case scenarios—from mild to severe—through the integration of multiple relevant features significantly enhances the model’s robustness and applicability in realistic offshore environments. The research demonstrates the potential of deep learning methods in advancing renewable energy technology, specifically in optimizing turbine efficiency, anticipating maintenance needs, and integrating wind power into energy grids. Full article

Offshore wind platforms face critical low-frequency vibration challenges requiring advanced isolation solutions. This work develops a quadrilateral-shaped vibration isolation platform (QVIP) with a quasi-zero stiffness property for floating structures, combining negative stiffness elements and optimized damping to achieve high-static-low-dynamic-stiffness. Theoretical modeling establishes the QVIP’s working principle and parametric behavior, while numerical simulations validate its ultra-low frequency (<1 Hz) suppression capabilities with time domain analysis. The design overcomes conventional trade-offs between low-frequency isolation and load-bearing capacity, offering improved stability for offshore applications compared to linear isolators. Results demonstrate effective vibration control through tailored nonlinear stiffness characteristics (e.g., 48.17% isolation efficiency, 39.48% peak amplitude reduction, and 73.14% variance reduction), suggesting practical viability for next-generation floating platforms. Full article