Search Results (681)

The energy transition in Ibero-American countries demands significant diversification, yet the vast potential of offshore renewable energies (ORE) remains largely untapped. Slow adoption is often attributed to the hostile marine environment, high investment costs, and a lack of institutional, regulatory, and industrial readiness. A critical barrier for policymakers is the absence of methodologically robust tools to assess national preparedness. Existing indices typically rely on simplistic weighting schemes or are susceptible to known flaws, such as the rank reversal phenomenon, which undermines their credibility for strategic decision-making. This study addresses this gap by developing a multi-criteria decision-making (MCDM) framework based on a problem-specific synthesis of established optimization principles to construct a comprehensive Offshore Readiness Index (ORI) for 13 Ibero-American countries. The framework moves beyond traditional methods by employing an advanced weight-elicitation model rooted in the Robust Ordinal Regression (ROR) paradigm to analyze 42 sub-criteria across five domains: Regulation, Planning, Resource, Industry, and Grid. Its methodological core is a non-linear objective function that synergistically combines a Shannon entropy term to promote a maximally unbiased weight distribution and to prevent criterion exclusion, with an epistemic regularization penalty that anchors the solution to expert-derived priorities within each domain. The model is guided by high-level hierarchical constraints that reflect overarching policy assumptions, such as the primacy of Regulation and Planning, thereby ensuring strategic alignment. The resulting ORI ranks Spain first, followed by Mexico and Costa Rica. Spain’s leadership is underpinned by its exceptional performance in key domains, supported by specific enablers, such as a dedicated renewable energy roadmap. The optimized block weights validate the model’s structure, with Regulation (0.272) and Electric Grid (0.272) receiving the highest importance. In contrast, lower-ranked countries exhibit systemic deficiencies across multiple domains. This research offers a dual contribution: methodological innovation in readiness assessment and an actionable tool for policy instruments. The primary policy conclusion is clear: robust regulatory frameworks and strategic planning are the pivotal enabling conditions for ORE development, while industrial capacity and infrastructure are consequent steps that must follow, not precede, a solid policy foundation. Full article

As the proportion of renewable energy generation in the power grid continues to rise, the operational state of the power system changes frequently with fluctuations in renewable power output. However, the traditional fixed-weight multi-objective reactive power optimization method lacks the necessary flexibility and adaptability, as it is unable to dynamically adjust the priority levels of different objectives based on real-time operating conditions (such as load fluctuations and changes in network structure). As a result, its optimization decisions may deviate from the system’s most urgent economic or security needs. To address this issue, this paper proposes an adaptive multi-objective reactive power optimization control method. The proposed approach formulates the objective function as the weighted sum of system active power loss and voltage deviation at the grid connection point, with weight coefficients adaptively adjusted based on the voltage deviation at the grid connection point. First, the relationship between voltage fluctuations at the offshore wind farm grid connection point and active/reactive power output is analyzed, and a corresponding reactive power allocation model is established. Second, taking into account the input–output characteristics of wind turbine generators and static var compensators, a reactive power control model is constructed. Third, considering offshore operational constraints such as power and voltage limits, a weighted variation particle swarm optimization algorithm (WVPSO) is developed to solve for the reactive power control strategy. Finally, the proposed method is validated through tests using a practical offshore wind farm as a case study. The test results demonstrate that, compared with the traditional fixed-weight multi-objective reactive power optimization approach, the proposed method can rapidly adjust the priority of each optimization objective according to the real-time grid conditions, achieving effective coordinated optimization of both active power loss and voltage at the grid connection point, and the voltage deviation is kept within 5%, even with power system fluctuations. In addition, compared with the traditional PSO algorithm, for various test situations, WVPSO exhibits above 15% improvement in solution speed and enhanced solution accuracy. Full article

The global transition towards sustainable energy has accelerated the development and deployment of offshore wind turbines. Jacket foundations, commonly installed in intermediate to deep water depths to access available space and higher load capacities, are built to withstand intensified hydrodynamic loads. Due to their structural complexity near the seabed, however, they are prone to local and global scour, which can compromise stability and increase maintenance costs. While extensive research has addressed scour protections around monopiles, limited attention has been given to complex foundation geometries or even hybrid configurations that combine energy-harvesting devices with structural support. These hybrid systems introduce highly unsteady flow fields and amplified turbulence effects that current design frameworks appear to be unable to capture. This study provides an experimental characterisation of scour damage in riprap-protected jackets as well as additional tests for a hybrid jacket foundation. A novel adaptation of a high-resolution overlapping sub-area methodology was employed. For the first time, it was successfully applied to quantify the damage to riprap protections for a complex offshore foundation. Results revealed that, although hybrid jackets showed the capacity to attenuate incident waves, the scour protection experienced damage numbers (S_3D) two to six times higher than conventional jackets due to flow amplifications. The findings highlight the need for revised design guidelines that can account for the complex hydrodynamic-structural interactions of next-generation marine harvesting technologies integrated into complex foundations. Full article

Energy security crises have historically been turning points for energy systems, exposing vulnerabilities, reshaping policy priorities, and boosting technological change. However, whether—and to what extent—such crises accelerate low-carbon transitions remains contested. This paper examines the effects of the 2022 energy crisis on the European Union (EU)’s energy transition, using policy analysis combined with a quantitative assessment of renewable energy trends, forecasts, and targets. We analyse the ambition, implementation, and outcomes of the REPowerEU plan, the main response to the crisis. In an unprecedented move, REPowerEU securitised renewable energy as a means to reduce dependence on Russian energy imports. However, the plan only moderately increased earlier renewable energy targets and did not reverse declining subsidies despite more forceful implementation measures. Its effects have been uneven across technologies. Already accelerating solar may overshoot its targets, onshore wind might only slightly accelerate beyond its current steady growth, and offshore wind remains constrained by economic and institutional uncertainties. Despite increased subsidies for fossil fuels, coal continued declining, oil remained stable, and natural gas dropped. Overall, REPowerEU sustained rather than transformed the EU’s low-carbon transition, illustrating both the potential and limits of accelerating decarbonisation under security crises. Full article

This paper presents a comprehensive techno-economic and environmental assessment of offshore wind-powered green hydrogen production systems in Egypt and Oman, two strategically located countries within the MENA region with substantial renewable energy potential. A 120 MW offshore wind farm configuration, employing Vestas 8 MW turbines, was simulated for each country and coupled with an electrolyzer system to evaluate electricity generation, hydrogen yield, system efficiency, and cost-effectiveness. The analysis shows that both Egypt and Oman achieve high annual capacity factors (51% and 49.7%, respectively), resulting in annual green hydrogen production of 11.5 million kg and 11.2 million kg. Despite Egypt’s more stable year-round wind profile and slightly lower Levelized Cost of Hydrogen (LCOH: $3.09/kg vs. $3.17/kg), Oman’s seasonal monsoon (Khareef) offers exceptional summer productivity, with peak capacity factors exceeding 74%. A dual-framework environmental assessment was conducted to quantify CO₂ emissions mitigation. In the first scenario, based on grid substitution, the systems could avoid up to 240,000 and 256,000 tonnes of CO₂ annually in Egypt and Oman, respectively. The second scenario evaluates emissions avoided by replacing conventional gray hydrogen, yielding reductions of 126,500 tCO₂/year and 123,200 tCO₂/year, respectively. These results highlight the flexibility of offshore hydrogen systems in addressing both electricity-sector and hydrogen-market decarbonization goals. Additionally, sensitivity analysis shows that increasing turbine hub height yields only marginal wind speed and cost improvements, suggesting limited economic justification under current site conditions. Overall, the study positions Egypt as a stable, year-round hydrogen producer and Oman as a high-output seasonal exporter, supporting a complementary regional strategy for green hydrogen leadership. Full article

Wave energy technology needs to be reliable, efficient, and environmentally sustainable. Therefore, life cycle assessment (LCA) is a critical tool in the design of marine renewable energy devices. However, LCA studies of floating type wave cycloidal rotors remain limited. This study builds on previous work by assessing the cradle-to-grave environmental impacts of a cycloidal rotor wave farm, incorporating updated material inventories, site-dependent energy production, and lifetime extension scenarios. The farm with the steel cyclorotor configuration exhibits a carbon intensity of 21.4 g ${\mathrm{CO}}_2$ eq/kWh and an energy intensity of 344 kJ/kWh, which makes it a competitive technology compared to other wave energy converters. Alternative materials, such as aluminium and carbon fibre, yield mass reductions but incur higher embodied emissions. Site deployment strongly influences performance, with global warming potential reduced by up to 50% in high-power-density sites, while extending the operational lifetime from 25 to 30 years further reduces the impact by 17%. Overall, the results highlight the competitive environmental performance of floating wave cycloidal rotors and emphasize the importance of material selection, site selection, and lifetime extension strategies in reducing life cycle impacts. Full article

During the global transition of energy structures toward renewable sources, offshore wind power has experienced rapid advancement, coinciding with increasingly complex wave environments. This study focuses on the wave conditions of an offshore wind farm project in Vietnam. A dual-nested numerical framework (WAVEWATCH III + SWAN) is established, integrated with 32-year (1988–2019) high-resolution WRF wind fields and fused bathymetry data (GEBCO + in situ measurements). This framework overcomes the limitations of short-term datasets (10–22 years) in prior studies and achieves 1′ × 1′ (≈1.8 km) intra-farm resolution—critical for capturing topographic modulation of waves. A systematic analysis of the regional wave climate characteristics is performed, encompassing wave roses, joint distributions of significant wave height and spectral peak period, wave–wind direction correlations, and significant wave height–wind speed relationships. Extreme value theory, specifically the Pearson Type-III distribution, is applied to estimate extreme wave heights and corresponding periods for return periods ranging from 1 to 100 years, yielding critical design wave parameters for wind turbine foundations and support structures. Key findings reveal that the wave climate is dominated by E–SE (90°–120°) monsoon-driven waves (60% of $H_s$ = 0.5–1.5 m), while extreme waves are uniquely concentrated at 120°—attributed to westward Pacific typhoon track alignment and long fetch. For the outmost site (A55, 7.18 m water depth), the 100-year return period significant wave height ($H_{s100}$ = 4.66 m, $T_{p100}$ = 13.05 s) is 38% higher than sheltered shallow-water sites (A28, $H_{s100}$ = 2.7 m), reflecting strong bathymetric control on wave energy. This study makes twofold contributions: (1) Methodologically, it validates a robust framework for long-term wave simulation in tropical monsoon–typhoon regions, combining 32-year high-resolution data with dual-nested models. (2) Scientifically, it reveals the directional dominance and spatial variability of waves in the Mekong estuary, advancing understanding of typhoon–wave–topography interactions. Practically, it provides standardized design parameters (compliant with DNV-OS-J101/IEC 61400-3) for offshore wind projects in Southeast Asia. Full article

The transition toward carbon neutrality is accelerating the deployment of renewable energy sources (RES), creating new challenges for power balance, stability, and renewable generation curtailment. In the Baltic States, this RES growth coincides with synchronization with the Central European Synchronous Area, which poses additional technical and operational challenges. This paper evaluates the integration of offshore wind farms (OWFs) into the Lithuanian power system for 2027 and 2035, focusing on their impact on system operation, transmission loading, power balance and power system strength. A methodology based on extrapolated historical hourly data is applied to assess Lithuanian power system security under large-scale RES penetration, identifying critical contingencies and lines most prone to overloading. Results indicate that in 2027, network overloads may occur under N–1 contingencies when OWF capacity reaches 1400 MW; higher capacities require curtailment to maintain the generation–load balance. In 2035, planned grid reinforcements eliminate N–1 overloads. However, in both years, system strength remains the limiting factor. With an admissible short-circuit ratio (SCR) of 3, the maximum allowable OWF capacity is 1141 MW in 2027 and 1582 MW in 2035 under N–1, and 562 MW and 1039 MW under N–2 conditions. Full article

Floating offshore wind turbines (FOWTs) are essential for meeting global renewable energy goals, yet their viability depends strongly on platform motion in harsh marine environments and the resulting influence on structural loading and the levelized cost of energy. This study examines the dynamic response of a 15 MW semi-submersible FOWT based on the IEA-15-240-RWT developed by NREL. The baseline UMaine VolturnUS-S platform is evaluated alongside two newly proposed variants, KSNU-1 15 MW and KSNU-2 15 MW, each equipped with distinct heave-plate configurations designed to enhance hydrodynamic damping while maintaining equal surface area for fair comparison. Hydrodynamic coefficients are obtained through potential-flow analysis using Ansys Aqwa, and fully coupled aero-hydro-servo-elastic simulations are conducted with OpenFAST. The performance of all platforms is assessed under two design load cases (DLCs): the fatigue limit state (FLS) and the ultimate limit state (ULS). The results show that both KSNU platforms achieve slight reductions in surge, sway, and heave motions, with KSNU-2 providing the most consistent improvement in vertical and horizontal stability. Rotational responses increase modestly but remain within acceptable limits. Overall, the KSNU-2 design demonstrates improved motion control without compromising energy output, offering a promising configuration for large-scale floating wind applications. Full article

The Digital Twins of the Ocean (DTOs) represent an emerging framework for monitoring, simulating, and predicting ocean dynamics, supporting a range of applications relevant to understanding and responding to the global climate system. By integrating large-scale, multi-sourced datasets with advanced numerical models, DTOs provide a powerful tool for climate science. This review examines the role of machine learning (ML) in advancing DTOs applications, addressing the limitations of traditional methodologies under current conditions of increasing data availability from satellites, in situ sensors, and high-resolution numerical models. We highlight how ML serves as a versatile tool for enhancing DTOs capabilities, including real-time forecasting, correcting model biases, and filling data gaps where conventional approaches fall short. Furthermore, we review surrogate models that aim to complement or replace traditional physical models, offering increasing accuracy and the appeal of much faster inference for forecasts, and the insertion of hybrid models, which couple physics-based simulations with ML algorithms and are proving to be continuously improving in accuracy for complex oceanographic tasks as bigger datasets become available and methodologies evolve. This paper provides a comprehensive review of ML applications within DTOs, focusing on key areas such as water quality and marine biodiversity, ports, marine pollution, fisheries, and renewable energy. The review concludes with a discussion of future research directions and the potential of ML to foster more robust and practical DTOs, ultimately supporting informed decision-making for sustainable ocean management. Full article

Modern smart cities face increasing pressure to invest in sustainable and reliable energy systems while navigating uncertainties arising from fluctuating market conditions, evolving technology landscapes, and diverse expert opinions. Traditional multi-criteria decision-making (MCDM) approaches often fail to fully represent these uncertainties as they typically rely on crisp inputs, lack temporal memory, and do not explicitly account for stochastic variability. To address these limitations, this study introduces a novel Stochastic Fractional Fuzzy Tensor (SFFT)-based Group Decision-Making framework. The proposed approach integrates three dimensions of uncertainty within a unified mathematical structure: fuzzy representation of subjective expert assessments, fractional temporal operators (Caputo derivative, $\alpha =0.85$) to model the influence of historical evaluations, and stochastic diffusion terms ($\sigma =0.05$) to capture real-world volatility. A complete decision algorithm is developed and applied to a realistic smart city renewable energy selection problem involving six alternatives and six criteria evaluated by three experts. The SFFT-based evaluation identified Geothermal Energy as the optimal choice with a score of 0.798, followed by Offshore Wind (0.722) and Waste-to-Hydrogen (0.713). Comparative evaluation against benchmark MCDM methods—TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), VIKOR (VIšekriterijumsko KOmpromisno Rangiranje), and WSM (Weighted Sum Model)—demonstrates that the SFFT approach yields more robust and stable rankings, particularly under uncertainty and model perturbations. Extensive sensitivity analysis confirms high resilience of the top-ranked alternative, with Geothermal retaining the first position in 82.4% of 5000 Monte Carlo simulations under simultaneous variations in weights, memory parameter ($\alpha \in [0.25,0.95]$), and noise intensity ($\sigma \in [0.01,0.10]$). This research provides a realistic, mathematically grounded, and decision-maker-friendly tool for strategic planning in uncertain, dynamic urban environments, with strong potential for deployment in wider engineering, management, and policy applications. Full article

Offshore wind farms (OWFs) represent an increasingly important renewable energy source, yet their environmental impacts, particularly underwater noise, require systematic study. Estimating the operational source level (SL) of a single turbine and predicting sound pressure levels (SPLs) at sensitive locations can be challenging. Here, we integrate a turbine SL prediction algorithm with open-source propagation models in a Jupyter Notebook (version 7.4.7) to streamline aggregated SPL estimation for OWFs. Species-specific audiograms and weighting functions are included to assess potential biological impacts. The tool is applied to four planned OWFs, two in the Canary region and two in the Belgian and German North Seas, under conservative assumptions. Results indicate that at 10 m/s wind speed, a single turbine’s SL reaches 143 dB re 1 µPa in the one-third octave band centered at 160 Hz. Sensitivity analyses indicate that variations in wind speed can cause the operational source level at 160 Hz to increase by up to approximately 2 dB re 1 µPa²/Hz from the nominal value used in this study, while differences in sediment type can lead to transmission loss variations ranging from 0 to on the order of 100 dB, depending on bathymetry and range. Maximum SPLs of 112 dB re 1 µPa are predicted within OWFs, decreasing to ~50 dB re 1 µPa at ~100 km. Within OWFs, Low-Frequency (LF) cetaceans and Phocid Carnivores in Water (PCW) would likely perceive the noise; National Marine Fisheries Service (NMFS) marine mammals’ auditory-injury thresholds are not exceeded, but behavioral-harassment thresholds may be crossed. Outside the farms, only LF audiograms are crossed. In high-traffic North Sea regions, OWF noise is largely masked, whereas in lower-noise areas, such as the Canary Islands, it can exceed ambient levels, highlighting the importance of site-specific assessments, accurate ambient noise monitoring and propagation modeling for ecological impact evaluation. Full article

The use of underwater vehicles, either remotely operated vehicles (ROVs) or autonomous underwater vehicles (AUVs), has become increasingly relevant in the operation and maintenance (O&M) routines of offshore wind farms. This article provides a critical review of how these platforms are being integrated into inspection and maintenance tasks, contributing not only to safer and more precise operations but also to greater autonomy in challenging marine environments. Beyond the technical and operational aspects, this review highlights their growing connection with artificial intelligence, digital twins, and multi-robot collaboration. The studies analyzed indicate a progressive shift away from conventional methods, traditionally dependent on crewed vessels and manual inspections, toward more automated, sustainable, and integrated approaches that align with the environmental and social commitments of the offshore wind sector. Finally, emerging trends and persisting obstacles, notably energy autonomy, are discussed, outlining the requirements for consolidating a robust, connected, and sustainability-oriented model for offshore maintenance. Full article

The global transition to renewable energy sources is essential to carbon neutrality and ensuring energy security. First, the paper presents a comprehensive literature review of the main technological breakthroughs in bioenergy, hydro energy, solar energy, onshore and offshore wind energy, ocean energy, and geothermal energy, selecting the latest papers published. Next, key scientific challenges, environmental and economic constraints, and future research priorities for each of the six renewable energies were outlined. Then, to emphasize the important contribution of renewable energies to total energy production and the proportions of each type of renewable energy, the evolution of global electricity generation from all six renewable sources between 2000 and 2023 was analyzed. Thus, in 2023, the global electricity generation weight of each renewable energy in total renewable energy ranks hydro energy (47.83%) first, followed by onshore and offshore wind energy (25.8%), solar energy (18.19%), bioenergy (7.07%), geothermal energy (1.1%), and ocean energy (0.01%). After that, the bibliometric analysis, conducted between 1 January 2021 and 1 October 2025 on the Web of Science (WoS) database and using the PRISMA approach and VOSviewer version 1.6.20 software, enabled the identification of the most cited papers, publications and citation number by WoS categories, topics, correlation with Sustainable Development Goals, authors’ affiliation, publication title, and publisher. Furthermore, the paper presents a network visualization of the link between co-occurrences and all keywords, imposing minimum thresholds of 10, 20, and 30 occurrences per keyword, and computes the network density based on the number of edges and nodes. Finally, additional analysis included the most used keywords in different co-occurrences, a word cloud of occurrences by total link strength, regression of occurrences versus total link strength, and correlations between citations and documents and between citations and authors. Carbon neutrality and a resilient energy future can only be achieved by integrating renewable sources into hybrid systems and optimized smart grids. Each technological progress stage will bring new challenges that must be addressed cost-effectively. Full article

Wind power is a major source of renewable energy, yet turbine performance is strongly influenced by atmospheric conditions and surrounding terrain. Several meteorological phenomena can hinder energy production, disrupt operations, and accelerate structural deterioration. This paper reviews three key atmospheric hazards affecting wind turbine systems: lightning, icing, and rain. For each phenomenon, the formation mechanisms, operational effects, and mitigation approaches are examined, with offshore-specific processes and conditions integrated directly into each hazard discussion. Building on this foundation, the review then analyses interactions between the hazards, their combined implications for turbine performance and maintenance, and the associated economic impacts. Comparisons of material behaviour across lightning, icing, and rain-erosion conditions are also incorporated. Finally, future research directions are proposed. Full article