Search Results (223)

This study assesses the feasibility and profitability of marine hybrid clusters, combining wave energy converters (WECs) and offshore wind turbines (OWTs) to power households and marine aquaculture. Researchers analyzed two coastal sites: La Serena, Chile, with high and consistent wave energy resources, and Ensenada, Mexico, with moderate and more variable wave power. Two WEC technologies, Wave Dragon (WD) and Pelamis (PEL), were evaluated alongside lithium-ion battery storage and green hydrogen production for surplus energy storage. Results show that La Serena’s high wave power (26.05 kW/m) requires less hybridization than Ensenada’s (13.88 kW/m). The WD device in La Serena achieved the highest energy production, while PEL arrays in Ensenada were more effective. The PEL-OWT cluster proved the most cost-effective in Ensenada, whereas the WD-OWT performed better in La Serena. Supplying electricity for seaweed aquaculture, particularly in La Serena, proves more profitable than for households. Ensenada’s clusters generate more surplus electricity, suitable for the electricity market or hydrogen conversion. This study emphasizes the importance of tailoring emerging WEC systems to local conditions, optimizing hybridization strategies, and integrating consolidated industries, such as aquaculture, to enhance both economic and environmental benefits. Full article

Digital twins (DTs) offer significant promise for condition-based maintenance of floating offshore wind turbines (FOWTs); however, existing solutions typically compromise either on physical rigor or real-time computational performance. This paper presents a real-time DT framework that resolves this trade-off by embedding a hydro-elastic reduced-order model (ROM) that accurately captures structural dynamics and fluid–structure interaction. Integrated in a cloud-ready Internet of Things architecture, the ROM reconstructs full-field displacements, von Mises stresses, and fatigue metrics with near real-time responsiveness. Validation on the 5 MW OC4-DeepCWind semi-submersible platform shows that the ROM reproduces finite-element (FEM) displacements and stresses with relative errors below 1%. A three-hour load case is solved in 0.69 min for displacements and 3.81 min for stresses on a consumer-grade NVIDIA RTX 4070 Ti GPU—over two orders of magnitude faster than the full FEM model—while one million fatigue stress histories (1000 hotspots × 1000 operating scenarios) are processed in 37 min. This efficiency enables continuous structural monitoring, rapid *what-if* assessments and timely decision-making for targeted inspections and adaptive control. By effectively combining physics-based reduced-order modeling with high-throughput computation, the proposed framework overcomes key barriers to DT deployment: computational overhead, physical fidelity and scalability. Although demonstrated on a steel platform, the approach is readily extensible to composite structures and multi-turbine arrays, providing a robust foundation for cost-effective and reliable deep-water wind-energy operations. Full article

Turbine blades are the most critical parts of aircraft engines. They are exposed to complex forces at the highest temperature and an aggressive environment. For this reason, the highest demands are placed on their structural quality. In single-crystalline nickel-based superalloy blades, the quality of the dendritic structure, crystal orientation, and local lattice parameter homogeneity is important because such properties affect the strength properties of the casting. For this reason, the structural attributes mentioned above were studied for novel, model-cored blades made of Ni-based superalloy. The blades were studied using scanning electron microscopy, the dedicated original X-ray Ω-scan method, the Laue diffraction, and the X-ray diffraction topography. The differences in the dendrites’ morphology and their array, revealing changes in dendrites’ arm size and arrangement, and changes in dendrites’ symmetry, were observed. Misoriented areas were identified, forming subgrains separated by low-angle boundaries. The location of the subgrains concerning the blade geometry and reasons for their creation were analyzed. The relation between the observed local changes in the lattice parameter and the creation of structural defects was determined. Aspects influencing the formation of structural defects that may reduce the durability of castings in specific areas of the cored blade airfoils have been discussed. Full article

This paper proposes a new Asymmetric Permanent Magnet Vernier Motor (A-PMVM) for low-speed high-torque applications. Unlike conventional symmetric V-shaped PMVMs (SV-PMVMs), the A-PMVM features irregular U-shaped magnet arrays composed of asymmetric V-shaped magnets. Finite element analysis confirms its superior performance: 10.6% higher torque (19.67 N·m vs. 17.78 N·m), 22% reduced PM volume (37,500 mm³ vs. 48,000 mm³), and 53% lower cogging torque (0.32 N·m vs. 0.68 N·m peak-peak). While exhibiting higher initial torque ripple ratio (8.65%), multi-objective optimization suppresses torque ripple ratio by 5.32% (from 8.65% to 8.19%), reduces cogging torque 12.5% (from 0.32 N·m to 0.28 N·m), and enhances torque by 0.76% (from 19.67 N·m to 19.82 N·m). The optimized A-PMVM achieves a significant reduction in cogging torque and torque ripple ratio, demonstrating significant potential for applications like wind turbines and electric vehicles. Additionally, this paper confirms that the proposed motor maintains consistent performance during both clockwise and counterclockwise operation. Full article

Flapping foils, inspired by the wing motions of birds and the swimming mechanisms of aquatic animals, offer a promising alternative to traditional turbines for extracting renewable energy from ambient flows found in nature. This study employs an immersed boundary-lattice Boltzmann method (IB-LBM) to numerically investigate the energy extraction performance of multiple flapping foils at a Reynolds number of 1100. Two staggered foils are systematically studied to identify the optimum spatial arrangements needed to achieve high energy-harvesting performance. The results show that the wake of the fore-foil mainly contributes to the negative performance of the hind-foil due to the loss of streamwise flow velocity, and the interaction between the two foils can enhance the energy-harvesting performance of the system, but cannot fully alleviate the effects of flow velocity loss. Therefore, the staggered arrangements, which help the hind-foil shed the wake, are essential to improve the energy-harvesting performance of the hind-foil. Comparable performance for the hind-foil is achieved at a horizontal gap of $2.5c$ and vertical gap of $2.5c$ with c being the chord length of the foil. The scaled-up systems, including three-, five-, and seven-foil configurations, are examined with gaps of $2.5c$ (horizontal) and $2.5c$ (vertical), and the results show that such ‘V’-shaped arrangements of these foils can achieve high energy-harvesting performance, with an enhancement up to $10.7\%$ when seven foils are used, by utilizing the high mean streamwise velocity at the boundary of the leader’s wake, confirming the versatility of the optimum staggered arrangements for flapping-foil arrays. Full article

The collection grid represents a relevant share of the total initial investments into a wind power plant. Planning/optimizing collection grids is a task that grows severely in complexity according to the size of the analyzed plant, i.e., its number of wind turbines. This paper enhances a well-known mixed-integer linear programming formulation based on the types of cables available for installation and meant for radial grids. More specifically, this work proposes valid constraints that tighten the search space and enable faster convergence. Results indicate that small wind power plants do not benefit from the novel constraints, whereas the time to solve medium and large plants can significantly decrease. However, comparisons against an alternative algorithm based on the flowing power reveal that the proposed enhancement to the cable type-based formulation does not make it the most computationally efficient. In studies regarding Thanet, a wind power plant with 100 wind turbines, the mean convergence time has decreased from 18% up to 85% for different cases when applying the proposed constraints to the cable type-based formulation. Nonetheless, such durations are 2 to 15 times more extensive than what is required by the power-based algorithm. Thus, this paper seeks to raise awareness regarding the assessed algorithms and aid in more efficient inter-array cabling optimization studies. Full article

This paper presents a comprehensive economic optimization of a grid-connected hybrid renewable energy system (HRES) enhanced with an electromagnetic frequency regulator (EFR) to improve frequency stability and provide clean and continuous electricity to the Macau City Campus while reducing dependence on fossil sources. The system includes photovoltaic (PV) arrays, wind turbines, battery storage, EFR, and a backup diesel generator. A genetic algorithm (GA) is employed to optimally size these components with the objective of maximizing the net present value (NPV) over the system’s lifetime. The GA implementation was validated on standard benchmark functions to ensure correctness and was finely tuned for robust convergence. Comprehensive sensitivity analyses of key parameters (discount rate, component costs, resource availability, etc.) were performed to assess solution robustness. The optimized design ($\mathrm{PV}\approx 35\mathrm{kWp}$, $\mathrm{WT}=30\mathrm{kW}$, $\mathrm{ESS}\approx 200\mathrm{kWh}$, and $\mathrm{EFR}=30\mathrm{kW}$) achieves a highly positive net present value of BRL 1.86 M in 2015 values (BRL 3.11 M in 2025) and discounted payback in approximately 9 years. A comparative assessment with the 2015 baseline project revealed up to a 10.1% enhancement in the net present value, underscoring the economic advantages of the optimized design. These results confirm the system’s strong economic viability and environmental benefits, providing a valuable guideline for future grid-connected hybrid energy systems. Full article

With the widespread integration of renewable energy sources such as wind and solar power into power systems, their inherent unpredictability and fluctuations present significant challenges to grid stability and security. To address these issues, Battery Energy Storage Systems (BESSs) offer an effective means of enhancing renewable energy absorption and improving the overall system efficiency. This study proposes a coordinated planning method based on the improved bat algorithm (IBA) to tackle the challenges associated with integrating renewable energy into distribution networks. A bi-level optimization framework is introduced to coordinate the planning and operation of the distributed generation (DG) and BESS. The upper-level model focuses on selecting optimal sites and determining the capacity of wind turbines, photovoltaic arrays, and storage systems from an economic perspective. The lower-level model optimizes the curtailment of wind and solar energy and minimizes network losses based on the upper-level planning outcomes. Additionally, the lower-level model also coordinates the dispatch between renewable energy generation and storage systems to ensure the reliable operation of the system. To effectively solve this bi-level optimization model, we have improved the conventional bat algorithm. Simulation results show that the improved bat algorithm not only significantly enhances the convergence speed but also improves the voltage stability, with the photovoltaic utilization rate reaching 90.27% and the wind energy utilization rate reaching 92.18%. These results highlight the practical advantages and success of the proposed method in optimizing renewable energy configurations. Full article

To investigate how sand erosion impacts the anti-icing performance of wind turbine blade surfaces, this study experimentally examines the individual and interactive effects of four key factors—the freezing temperature, separation temperature, surface roughness of eroded blade coatings, and loading rate on ice adhesion properties.The results from single-factor analyses reveal that the ice adhesion strength increases linearly with decreasing separation temperature. A more nuanced relationship emerges when considering the freezing temperature relative to the separation temperature: when the freezing temperature exceeds the separation temperature, the adhesion strength rises linearly as the separation temperature drops; conversely, when the freezing temperature is lower than the separation temperature, the adhesion strength decreases linearly with falling separation temperature. Higher loading rates correlate with reduced ice adhesion, while increased surface roughness induced by sand erosion leads to greater adhesion strength. Orthogonal array testing demonstrates the hierarchy of these factors’ influence on post-erosion ice adhesion, as follows: separation temperature > loading rate > freezing temperature > surface roughness of sand-eroded coatings. Notably, the separation temperature and loading rate exert the most significant effects. Furthermore, a regression equation for ice adhesion strength is established based on orthogonal test results, which can effectively predict ice adhesion strength under untested parameter combinations. These findings provide critical foundational data and a reliable theoretical tool to inform the development and optimization of practical de-icing systems in engineering applications. Full article

This study investigates the downstream wake characteristics of a helical hydrokinetic turbine through combined experimental and numerical analyses. A four-bladed helical turbine with a 20 cm rotor diameter and blockage ratio of 53.57% was tested in an open water channel under a flow rate of 180 m³/h, corresponding to a Reynolds number of approximately 90 × 10³. Velocity measurements were collected at 13 downstream cross-sections using an Acoustic Doppler Velocimeter, with each point sampled repeatedly. Standard error analysis was applied to quantify measurement uncertainty. Complementary numerical simulations were conducted in ANSYS Fluent using a steady-state k-ω Shear Stress Transport (SST) turbulence model, with a mesh of 4.7 million elements and mesh independence confirmed. Velocity deficit and turbulence intensity were employed as primary parameters to characterize the wake structure, while the analysis also focused on the recovery of cross-sectional velocity profiles to validate the extent of wake influence. Experimental results revealed a maximum velocity deficit of over 40% in the near-wake region, which gradually decreased with downstream distance, while turbulence intensity exceeded 50% near the rotor and dropped below 10% beyond 4 m. In comparison, numerical findings showed a similar trend but with lower peak velocity deficits of 16.6%. The root mean square error (RMSE) and mean absolute error (MAE) between experimental and numerical mean velocity profiles were calculated as 0.04486 and 0.03241, respectively, demonstrating reasonable agreement between the datasets. Extended simulations up to 30 m indicated that flow profiles began to resemble ambient conditions around 18–20 m. The findings highlight the importance of accurately identifying the downstream distance at which the wake effect fully dissipates, as this is crucial for determining appropriate inter-turbine spacing. The study also discusses potential sources of discrepancies between experimental and numerical results, as well as the limitations of the modeling approach. Full article

As with wind turbines, marine tidal turbines are expected to be deployed in arrays of multiple turbines. To optimize these arrays, a more profound understanding of the interactions between turbines is necessary. This paper employs the Actuator Line Method alongside the Lattice Boltzmann Method and Large Eddy Simulation to develop a numerical model of tidal turbine arrays. It studies a vertical-axis turbine manufactured by HydroQuest/CMN that is equipped with two counter-rotating columns, each comprising two rotors. The ambient turbulence and upstream velocity profiles correspond to the characteristics of a tidal site such as the Alderney Race. Six turbine layouts are modeled: three aligned layouts with three turbines and three staggered layouts with four turbines. The spacing between turbines varies depending on the layout. This study yields several observations regarding array configuration. A minimum distance of 300 m, or $12D_{eq}$, between aligned turbines is necessary for full wake recovery. At shorter distances, the accumulation of velocity deficits significantly decreases the efficiency of the third turbine in the array. Pairs of counter-rotating vortices are observed in the wake of turbines. The evolution of these vortices and their influence on the wake depend greatly on the array configuration. An optimal configuration is observed in which the overall averaged power is not impaired by the interactions. Full article

The wind turbine blade is subject to multi-source impacts, such as bird strikes, lightning strikes, and hail, throughout its extended service. Accurate localization of those impact sources is a key technical link in structural health monitoring of the wind turbine blade. In this paper, a single-sensor impact source localization method is proposed. Capitalizing on deep learning frameworks, this method innovatively transforms the impact source localization problem into a classification task, thereby eliminating the need for anisotropy compensation and correction required by conventional localization algorithms. Furthermore, it leverages the inherent coding effects of the blade’s material and geometric anisotropy on impact sources originating from different positions, enabling localization using only a single sensor. Experimental results show that the method has a high localization accuracy of 96.9% under single-sensor conditions, which significantly reduces the cost compared to the traditional multi-sensor array scheme. This study provides a cost-effective solution for real-time detection of wind turbine blade impact events. Full article

Off-grid and isolated rural communities in developing countries with limited resources require energy supplies for daily residential use and social, economic, and commercial activities. The use of data from space assets and space-based solar power is a feasible solution for addressing ground-based energy insecurity when harnessed in a hybrid manner. Advances in space solar power systems are recognized to be feasible sources of renewable energy. Their usefulness arises due to advances in satellite and space technology, making valuable space data available for smart grid design in these remote areas. In this case study, an isolated village in Namibia, characterized by high levels of solar irradiation and limited wind availability, is identified. Using NASA data, an autonomous hybrid system incorporating a solar photovoltaic array, a wind turbine, storage batteries, and a backup generator is designed. The local load profile, solar irradiation, and wind speed data were employed to ensure an accurate system model. Using HOMER Pro software V 3.14.2 for system simulation, a more advanced AI optimization was performed utilizing Grey Wolf Optimization and Harris Hawks Optimization, which are two metaheuristic algorithms. The results obtained show that the best performance was obtained with the Grey Wolf Optimization algorithm. This method achieved a minimum energy cost of USD 0.268/kWh. This paper presents the results obtained and demonstrates that advanced optimization techniques can enhance both the hybrid system’s financial cost and energy production efficiency, contributing to a sustainable electricity supply regime in this isolated rural community. Full article

This study presents a multi-objective predictive energy management system (EMS) for optimizing hybrid renewable energy systems (HRES) in autonomous marine vessels. The objective is to minimize fuel consumption and emissions while maximizing renewable energy usage and pure-electric sailing durations. The EMS combines nonlinear model predictive control (NMPC) with metaheuristic optimizers—Grey Wolf Optimization (GWO) and Genetic Algorithm (GA)—and is benchmarked against a conventional rule-based (RB) method. The HRES architecture comprises photovoltaic arrays, vertical-axis wind turbines (VAWTs), diesel engines, generators, and a battery storage system. A ship dynamics model was used to represent propulsion power under realistic sea conditions. Simulations were conducted using real-world operational and environmental datasets, with state prediction enhanced by an Extended Kalman Filter (EKF). Performance is evaluated using marine-relevant indicators—fuel consumption; emissions; battery state of charge (SOC); and emission cost—and validated using standard regression metrics. The NMPC-GWO algorithm consistently outperformed both NMPC-GA and RB approaches, achieving high prediction accuracy and greater energy efficiency. These results confirm the reliability and optimization capability of predictive EMS frameworks in reducing emissions and operational costs in autonomous maritime operations. Full article

Power output and economic cost are two critical factors influencing the layout of tidal stream turbine arrays. To identify the optimal configuration, this study establishes a two-objective optimization framework that simultaneously considers these factors. Both the spatial location and yaw angle of each turbine are optimized to enhance overall power output, while the total length of submarine cables, which is used to transmit electricity from the turbines to the onshore power station, is adopted as the metric for economic cost. The Huludao water area is selected as the study domain. A 12-turbine array is examined under varying weight coefficients to investigate the trade-off between maximizing power output and minimizing economic cost. The optimization results show that submarine cable length decreases linearly as its economic weight coefficient increases, while the array’s power output exhibits a stepwise decline. This indicates that, with carefully chosen weight coefficients, economic costs can be significantly reduced without a proportional sacrifice in power output. Furthermore, increasing the number of turbines connected by a single cable not only enhances power output but also reduces total cable length, thereby improving the overall profitability of the optimized array layout. Full article