Search Results (618)

In recent years, the twin-barge float-over method has been widely used in offshore installations. This paper conducts numerical simulation and experimental research on the twin-barge float-over installation of offshore wind turbines (TBFOI-OWTs), focusing primarily on seakeeping performance, and also explores the influence of the gap distance on the hydrodynamic behavior of TBFOI-OWTs. Model tests are conducted in the ocean basin at Tsinghua Shenzhen International Graduate School. A physical model with a scale ratio of 1:50 is designed and fabricated, comprising two barges, a truss carriage frame, two small wind turbines, and a spread catenary mooring system. A series of model tests, including free decay tests, regular wave tests, and random wave tests, are carried out to investigate the hydrodynamics of TBFOI-OWTs. The experimental results and the numerical results are in good agreement, thereby validating the accuracy of the numerical simulation method. The motion RAOs of TBFOI-OWTs are small, demonstrating their good seakeeping performance. Compared with the regular wave situation, the surge and sway motions in random waves have greater ranges and amplitudes. This reveals that the mooring analysis cannot depend on regular waves only, and more importantly, that the random nature of realistic waves is less favorable for float-over installations. The responses in random waves are primarily controlled by motions’ natural frequencies and incident wave frequency. It is also revealed that the distance between two barges has a significant influence on the motion RAOs in beam seas. Within a certain range of incident wave periods (10.00 s < T < 15.00 s), increasing the gap distance reduces the sway RAO and roll RAO due to the energy dissipated by the damping pool of the barge gap. For installation safety within an operating window, it is meaningful but challenging to have accurate predictions of the forthcoming motions. For this, this study employs the Whale Optimization Algorithm (WOA) to optimize the Long Short-Term Memory (LSTM) neural network. Both the stepwise iterative model and the direct multi-step model of LSTM achieve a high accuracy of predicted heave motions. This study, to some extent, affirms the feasibility of float-over installation in the offshore wind power industry and provides a useful scheme for short-term predictions of motions. Full article

Urban distributed energy systems play a crucial role in the development of sustainable and low-carbon cities. Evaluating urban wind resources is essential for effective wind energy harvesting, which requires detailed information about the urban flow field. Computational fluid dynamics (CFD) has emerged as a viable and scalable method for assessing urban wind resources. This review paper synthesizes the characteristics of the urban wind environment and resources, outlines the general framework for CFD-aided wind resource assessment, and addresses future challenges and perspectives. It highlights the critical need to optimize wind energy harvesting in complex built environments. The paper discusses the conditions for urban wind resource assessment, particularly the extraction of boundary conditions and the performance of small wind turbines (SWTs). Additionally, it notes that while large eddy simulation (LES) is a high-fidelity model, it is still less commonly used compared to Reynolds-averaged Navier–Stokes (RANS) models. Several challenges remain, including the broader adoption of high-fidelity LES models, the integration of wake models and extreme conditions, and the application of these methods at larger scales in real urban environments. The potential of multi-scale modeling approaches to enhance the feasibility and scalability of these methods is also emphasized. The findings are intended to promote the utilization and further development of CFD methods to accelerate the creation of resilient and energy-efficient cities, as well as to foster interdisciplinary innovation in wind energy systems. Full article

The sub-synchronous oscillation (SSO) characteristics and suppression strategies of a hybrid system comprising doubly fed induction generator (DFIG)-based wind turbines and synchronous pumped storage units connected to the power grid via series-compensated transmission lines are analyzed. A modular modeling approach is used to construct a detailed system model, including the wind turbine shaft system, DFIG, converter control system, synchronous machine, excitation system, power system stabilizer (PSS), and series-compensated transmission lines. Eigenvalue calculation-based small-signal stability analysis is conducted to identify the dominant oscillation modes. Suppression measures are also developed using relative participation analysis, and simulations are carried out to validate the accuracy of the model and analysis method. The analysis results indicate that the SSO phenomenon is primarily influenced by the electrical state variables of the DFIG system, while the impact of the state variables of the synchronous machine is relatively minor. When the level of series compensation in the system increases, SSO is significantly exacerbated. To address this issue, a sub-synchronous damping controller (SSDC) is incorporated on the rotor side of the DFIG. The results demonstrate that this method effectively mitigates the SSO and significantly enhances the system’s robustness against disturbances. Furthermore, a simplified modeling approach is proposed based on relative participation analysis. This method neglects the dynamic characteristics of the synchronous machine while considering its impact on the steady-state impedance and initial conditions of the model. These findings provide theoretical guidance and practical insights for addressing and mitigating SSO issues in hybrid renewable energy systems composed of DFIGs and synchronous machines. Full article

This study explores the potential of wind energy to address electricity shortages in South Africa, focusing on the Ekuphumleni community in Whittlesea. Given the challenges of expanding the national grid to these areas, wind energy is considered to be a feasible alternative to provide clean, renewable energy and reduce fossil fuel dependence in this community. This research evaluates wind potential utilizing the two-parameter Weibull distribution, with scale and shape parameters estimated by five traditional numerical methods and one metaheuristic optimization technique: whale optimization algorithm (WOA). Goodness-of-fit tests, such as the coefficient of determination (R²) and wind power density error (WPDE), were utilized to determine the best method for accurately estimating Weibull scale and shape parameters. Furthermore, net fitness, which combines R² and WPDE, was employed to provide a holistic assessment of overall performance. Whittlesea showed moderate wind speeds, averaging 3.88 m/s at 10 m above ground level (AGL), with the highest speeds in winter (4.87 m/s) and optimum in July. The WOA method outperformed all five numerical methods in this study in accurately estimating Weibull distribution parameters. Interestingly, the openwind method (OWM), a numerical technique based on iterative methods, and the Brent method showed comparable performance to WOA. The wind power density was 67.29 W/m², categorizing Whittlesea’s potential as poor and suitable for small-scale wind turbines. The east wind patterns favor efficient turbine placement. The study recommends using augmented wind turbines for the site to maximize energy capture at moderate speeds. Full article

This study examines output energy and efficiency of a torsional flutter harvester in gusty winds. The proposed apparatus exploits the torsional flutter of a rigid flapping foil, able to rotate about a pivot axis located in the proximity of the windward side. The apparatus operates at the “meso-scale”; i.e., the apparatus’ projected area is equal to a few square meters. It has unique properties in comparison with most harvesting devices and small wind turbines. The reference geometric chord length of the flapping foil is about one meter. Energy conversion is achieved by an adaptable linkage connected to a permanent magnet that produces eddy currents in a multi-loop winding coil. Operational conditions and the post-critical flutter regime are investigated by numerical simulations. Several configurations are examined to determine the output power and to study the effects of stationary turbulent flows on the energy-conversion efficiency. This paper is a continuation of recent studies. The goal is to examine the operational conditions of the apparatus for a potentially wide range of applications and moderate mean wind speeds. Full article

Tower bolts play a crucial role as connecting components in wind turbines and are of great interest for health monitoring systems. Non-contact monitoring techniques offer superior efficiency, convenience, and intelligence compared to contact-based methods. However, the precision and robustness of the non-contact monitoring process are significantly impacted by suboptimal lighting conditions within the wind turbine tower. To address this problem, this article proposes an automated detection method for the bolt detachment of wind turbines in low-light scenarios. The approach leverages the deep convolutional generative adversarial network (DCGAN) to expand and augment the small-sample bolt dataset. Transfer learning is then applied to train the Zero-DCE++ low-light enhancement model and the bolt defect detection model, with the experimental verification of the proposed method’s effectiveness. The results reveal that the deep convolutional generative adversarial network can generate realistic bolt images, thereby improving the quantity and quality of the dataset. Additionally, the Zero-DCE++ light enhancement model significantly increases the mean brightness of low-light images, resulting in a decrease in the error rate of defect detection from 31.08% to 2.36%. In addition, the model’s detection performance is affected by shooting angles and distances. Maintaining a shooting distance within 1.6 m and a shooting angle within 20° improves the reliability of the detection results. Full article

This study investigates the integration of three types of vertical-axis wind turbines (VAWTs)—helical, IceWind, and a combined design—on residential buildings in Çeşme, Türkiye, a region with an average wind speed of 7 m/s. The research explores the potential of small-scale wind turbines in urban areas, providing sustainable solutions for renewable energy generation and reducing reliance on conventional energy sources. The turbines were designed and analyzed using SolidWorks and ANSYS Fluent, achieving power outputs of 350 W for the helical turbine, 430 W for the IceWind turbine, and 590 W for the combined turbine. A total of 42 turbines were mounted on a five-storey residential building model, and DesignBuilder software was utilized to simulate and evaluate the energy consumption. The baseline energy consumption of 172 kWh/m² annually was reduced by 18.45%, 22.93%, and 30.88% for the helical, IceWind, and combined turbines, respectively. Furthermore, the economic analysis showed payback periods of 12.89 years for the helical turbine, 10.60 years for the IceWind turbine, and 10.49 years for the combined turbine. These findings emphasize the viability of integrating VAWTs into urban buildings as an effective strategy for reducing energy consumption, lowering costs, and enhancing energy efficiency. Full article

This study introduces a new method to locate cracks in wind turbine blades using the support vector machine algorithm and the tangential vibration signal measured at the root blade in static conditions. The method was implemented in hardware and experimentally validated on 200 W wind turbine blades. The blade conditions were healthy, and transverse cracked at the root, midsection, and tip. The experimental procedure is easy, and only one low-cost piezoelectric accelerometer is needed, which is affordable and straightforward to install. The machine learning technique used requires a small dataset and low computing power. The results show exceptional performance, achieving an accuracy of 99.37% and a precision of 98.77%. This approach enhances the reliability of wind turbine blade monitoring. It provides a robust early detection and maintenance solution, improving operational efficiency and safety in wind energy production. K-nearest neighbors and decision trees are also used for comparison purposes. Full article

Green hydrogen plays a vital role in facilitating the transition to sustainable energy systems, with stable and high-capacity offshore wind resources serving as an ideal candidate for large-scale green hydrogen production. However, as the capacity of offshore wind turbines continues to grow, the increasing size and weight of these systems pose significant challenges for installation and deployment. This study investigates the application of high-temperature superconducting (HTS) materials in the generator and the power conducting cables as a promising solution to these challenges. Compared to conventional wind turbines, HTS wind turbines result in significant reductions in weight and size while simultaneously enhancing power generation and transmission efficiency. This paper conducts a comprehensive review of mainstream electrolysis-based hydrogen production technologies and advanced hydrogen storage methods. The main contribution of this research is the development of an innovative conceptual framework for a superconducting offshore wind-to-hydrogen energy system, where a small amount of liquid hydrogen is used to provide a deep-cooling environment for the HTS wind turbine and the remaining liquid hydrogen is used for the synthesis of ammonia as a final product. Through functional analysis, this study demonstrates its potential for enabling large-scale offshore hydrogen production and storage. Additionally, this paper discusses key challenges associated with real-world implementation, including optimizing the stability of superconducting equipment and ensuring component coordination. The findings offer crucial insights for advancing the offshore green hydrogen sector, showing that HTS technology can significantly enhance the energy efficiency of offshore wind-to-hydrogen systems. This research provides strong technical support for achieving carbon neutrality and fostering sustainable development in the offshore renewable energy sector. Full article

In this study, we conducted experimental and numerical investigations of a Darrieus rotor with asymmetrical blades, which has two structural configurations—with and without horizontal parallel plates. Experimental tests were conducted in a wind tunnel at various air flow velocities (ranging from 3 m/s to 15 m/s), measuring rotor rotation frequency, torque, and thrust force. The computational simulation used the ANSYS 2022 R2 Fluent software package, where CFD simulations of air flow around both rotor configurations were performed. The calculations employed the Realizable k-ε turbulence model, while an unstructured mesh with local refinement in the blade–flow interaction zones was used for grid generation. The study results showed that the rotor with horizontal parallel plates exhibits higher aerodynamic efficiency at low wind velocities compared to the no-plates rotor. The experimental findings indicated that at wind speeds of 3–6 m/s, the rotor with plates demonstrates 18–22% higher torque, which facilitates the self-start process and stabilizes turbine operation. The numerical simulations confirmed that horizontal plates contribute to stabilizing the air flow by reducing the intensity of vortex structures behind the blades, thereby decreasing aerodynamic drag and minimizing energy losses. It was also found that the presence of plates creates a directed flow effect, increasing the lift force on the blades and improving the power coefficient (Cp). In the case of the rotor without plates, the CFD simulations identified significant low-pressure zones and high turbulence regions behind the blades, leading to increased aerodynamic losses and reduced efficiency. Thus, the experimental and numerical modeling results confirm that the Darrieus rotor with horizontal parallel plates is a more efficient solution for operation under low and variable wind conditions. The optimized design with plates ensures more stable flow, reduces energy losses, and increases the turbine’s power coefficient. These findings may be useful for designing small-scale wind energy systems intended for areas with low wind speeds. Full article

In Germany, wind and photovoltaic (PV) systems dominate renewable electricity generation, with large wind turbines contributing 24.1% and PV systems contributing 10.6% in 2022. In contrast, electricity production from small wind turbines remains marginal (<0.01%). While currently only viable in high-wind locations, factors like rising electricity prices, cheaper battery storage, and increasing electrification could boost their future role. Within this work, a residential energy supply system consisting of a small wind turbine, PV system, heat pump, battery storage, and electric vehicle was dimensioned for different sites in Germany and Canada based on detailed simulation models and genetic algorithms in order to analyze the effect of bidirectional charging on optimal system dimensions and economic feasibility. This was carried out for various electricity pricing conditions. The results indicate that, with electricity purchase costs above 0.42 EUR/kWh, combined with a 25% reduction in small wind turbine and battery storage investment expenses, economic viability could be significantly enhanced. This might expand the applicability of small wind power to diverse sites. Full article

With the increase in installed capacity of wind turbines, the stable operation of the power system has been affected. Accurate prediction of wind power is an important condition to ensure the healthy development of the wind power industry and the safe operation of the power grid. This paper first introduces the current status of wind power prediction methods under normal weather, and introduces them in detail from three aspects: physical model method, statistical prediction method and combined prediction method. Then, from the perspectives of numerical simulation analysis and statistical prediction methods, the wind power prediction method under icy conditions is introduced, and the problems faced by the existing methods are pointed out. Then, the accurate prediction of wind power under icing weather is considered, and two possible research directions for wind power prediction under icy weather are proposed: a statistical prediction method for classifying and clustering wind turbines according to microtopography, combining large-scale meteorological parameters with small-scale meteorological parameter correlation models and using machine learning for cluster power prediction, and a power prediction model converted from the power prediction model during normal operation of the wind turbine to the power prediction model during icing. Finally, the research on wind power prediction under ice-covered weather is summarized, and further research in this area is prospected. Full article

This study explores the integration of wind power generation into urban infrastructure via a rooftop vertical-axis wind turbine. A rigorous experimental framework was established by installing a small-scale turbine on an urban building for performance assessment under controlled conditions. Simulated environmental conditions were created using a pedestal fan and blower to evaluate mechanical interactions between the components and electrical output efficiency of the turbine. Extensive numerical modeling was conducted to analyze turbine performance, by computational fluid dynamics using ANSYS FLUENT. The results reveal that the turbine operates efficiently even at low to moderate wind speeds (0.5–6 m/s), demonstrating its feasibility for urban deployment. Performance tests indicated that, as the shaft rotational speed increased from 55 rpm to 115 rpm, the output voltage, current and power varied nonlinearly in the ranges of 3–11.9 V, 20–130 mA and 0.05–2.7 W, respectively. Vibration measurement at specified turbine locations revealed nonlinear variation in displacement, velocity, acceleration and frequency without fixed patterns. Good agreement was observed between the experimental and numerical results. The numerical model yielded interesting profiles related to velocity and turbulence distributions, apart from torque, mechanical power and electrical voltage. Important conclusions were drawn from the entire work. Full article

Recent results indicate that the characteristic locus method provides a convenient approach for analyzing power system low-frequency stability. In this study, an enhanced version of the method, referred to as the inverse characteristic locus method, is introduced. By inverting the similarity matrix of the loop transfer function matrix of the system, a more reliable and accurate stability metric is obtained. The proposed method is applied to assess the impact of changes in wind turbine generator (WTG) dynamics and system operating conditions on stability. Simulation results demonstrate that variations in system operating conditions exert a greater influence on stability compared to changes in WTG dynamics. Full article

This paper takes a four-point contact ball bearing of a wind turbine as the research object, analyzes the force and deformation relationship under the combined action of axial load and radial load, obtains the load distribution of rolling elements, and establishes a time-varying stiffness model of four-point contact ball bearings without clearance. The stiffness variation law of the case bearing in one rolling period is analyzed, and the time-varying characteristics of stiffness are characterized by the average stiffness and stiffness amplitude variation rate. The influence laws of the number of rolling elements, initial contact angle, axial load, and radial load on the time-varying characteristics of bearing stiffness are analyzed. The results show that within one rolling period, the average value of axial stiffness is about 2.21 times that of radial stiffness, and the amplitude variation rates of radial stiffness and axial stiffness are 0.0047% and 0.002%, respectively. The time-varying characteristics of both are not obvious. The influence of the number of rolling elements on the two stiffnesses is almost linear, while the influence of axial load on stiffness is small; the initial contact angle is positively correlated with axial stiffness and negatively correlated with radial stiffness. With the increase in radial load, the two stiffnesses also increase. Finally, the stiffness test of four-point contact ball bearings was carried out, and the error between the test value and the theoretical value was less than 15%, which preliminarily verified the correctness of the stiffness model. Full article