Search Results (9,000)

The wind–solar–storage–thermal combined power generation system is one of the key measures for China’s energy structure transition, and rational capacity planning of each generation entity within the system is of critical importance. First, this paper addresses the uncertainty of wind and photovoltaic (PV) power outputs through scenario-based analysis. Considering the diversity of generation entities and their complex interest demands, a bi-level capacity optimization framework based on game theory is proposed. In the upper-level framework, a game-theoretic method is designed to analyze the multi-agent decision-making process, and the objective function of capacity allocation for multiple entities is established. In the lower-level framework, multi-objective optimization is performed on utility functions and node voltage deviations. The Nash equilibrium of the non-cooperative game and the Shapley value of the cooperative game are solved to study the differences in the capacity allocation, economic benefits, and power supply stability of the combined power generation system under different game modes. The case study results indicate that under the cooperative game mode, when the four generation entities form a coalition, the overall system achieves the highest supply stability, the lowest carbon emissions at 30,195.29 tons, and the highest renewable energy consumption rate at 53.93%. Moreover, both overall and individual economic and environmental performance are superior to those under the non-cooperative game mode. By investigating the capacity configuration and joint operation strategies of the combined generation system, this study effectively enhances the enthusiasm of each generation entity to participate in the energy market; reduces carbon emissions; and promotes the development of a more efficient, environmentally friendly, and economical power generation model. Full article

A polyethylene pipe reinforced with winding steel wires (PSP) is a new composite pipe in which steel wires are effectively bonded with high-density polyethylene (HDPE) through hot-melt adhesive, ensuring the mechanical properties and structural integrity of the pipe. One of the main failure modes at the PSP joint is the interfacial debonding between the steel wire and the hot-melt adhesive. To find a good method to overcome this debonding failure mode, the first priority is to be able to quantitatively characterize the interface performance. Thus, in this study, double cantilever beam (DCB) tests are used to investigate the interfacial properties between steel and hot-melt adhesive, and a finite element model with cohesive element representing the adhesive interface is established to analyze the interfacial properties and the interfacial failure process. However, the interfacial parameters, including interface strength and fracture energy, cannot be obtained directly; thus, based on the inverse optimization calculation concept, an ABAQUS–Python–MATLAB interactive program is developed to continuously optimize and adjust the key parameters of the interface during iterative calculations so that the load–displacement simulation curve is close to the experimental curve, thereby determining the solution set of interface strength and fracture energy. With the inversion parameters substituted into the DCB model, the simulated reaction force–displacement curve is obtained, and it is consistent with the experimental one. Furthermore, this paper compares the pattern of simulated crack tip propagation during the loading process with the experimental results, and it is found that the simulated curve agrees well with the trends of the experimental ones. This proves the effectiveness of the DCB finite element model and the inversion calculation method from a new perspective, indicating that the simulation results of the DCB model were consistent with the experiment. This method can provide guidance and reference for the mechanical behavior analysis of the bonding interface of other materials or structures. Full article

The wind environment in furnace cities has attracted considerable research attention. Investigating the impact of suburban residential building arrangements in furnace cities on inter-building wind speed fields is useful and cost-effective for scientifically optimizing layouts. This study simulated 13 wind speed fields across six symmetric and asymmetric building arrangements: linear, inclined, convex, concave, M-shaped, and V-shaped, with varying building offsets and spacing widths. We used the standard k–ε model for simulations through finite element method. Results demonstrated that larger building offsets enhanced inter-building wind speeds, with the concave arrangement most effectively enhanced the wind speed between buildings among the configurations. V-shaped arrangements slightly underperformed concave layouts in wind speed uniformity. Based on the summer wind direction data from Wuhan Tianhe Meteorological Station, we propose two corresponding layouts: concave and V-shaped arrangements, which are conductive to enhancing inter-building wind speed. In practical planning, the orientation of building clusters can be adjusted according to the local wind rose diagram. Full article

With the increasing intelligence of modern air-conditioning systems, the difficulty of acquiring data from air-conditioning systems has been significantly reduced. However, analyzing the massive amounts of data collected and obtaining more valuable information still remains challenging, especially considering the internal relationships behind the data. The purpose of this study was to conduct operational experiments on VRF systems under different indoor set temperatures, indoor set air speeds, and terminal load rates. Then, the patterns of various operating parameters and energy consumption of VRF systems during winter operation were analyzed based on unsupervised methods. Three machine learning methods were primarily employed in this study, including correlation analysis, data regression analysis, and association rule analysis. Finally, a regression model was constructed for energy consumption based on eight typical characteristic parameters. The experimental results showed that the system was stable to a certain degree at different wind speeds. Among the characteristic parameters, fixed frequency 1 exhaust temperature, compressor frequency, and other parameters have a significant positive effect on energy consumption, while fixed frequency 1 shell top oil temperature, inlet and outlet pipe temperature difference, and other parameters have a negative effect. The research results provide a reference for air conditioning system data mining and building sustainability. Full article

Objectives: SailGP is an international professional mixed-sex sailing competition, which uses F50 foiling catamarans capable of reaching speeds up to ~100 km/h. This seminal study assesses injuries and illnesses observed by male and female sailors during trainings and competitions in SailGP’s third season. This study aims to assess injury and illness incidence, comparing results with other professional sailing events and high-performance sports. In addition, injury and illness risk factors (sex and position) will be explored with the goal to reduce morbidity for future seasons. Materials and Methods: This retrospective cohort design analysed medical records of male and female sailors during SailGP’s third season (April 2022 to May 2023). Risk factors assessed included sailor sex, sailor position (helm, strategist, grinder, flight controller and wing trimmer), sailing venue, wind speed and mechanism of injury/nature of illness. International Olympic Committee reporting guidelines on injuries and illnesses were followed, including the STROBE-SIIS checklist. Confidence intervals were set at 95%, statistical tests were two-sided and p-values < 0.05 were considered statistically significant. Results: A total of 40 on-water injuries were reported in 32 athletes. Injury incidence was greater during competitions than trainings, with strategists and then grinders being the most frequently injured positions. Competition injury incidence was 32.6 per 1000 h and 6.42 injuries per 365 days. Training injury incidence was 2.62 injuries per 1000 h and 3.82 injuries per 365 days. Knee, ankle, hand and head injuries were most prevalent, with three concussions observed during trainings and competitions (two female and one male). Direct impacts and falls during manoeuvres caused most injuries. Overall injury incidence (IRR = 2.69 [95% CI 1.41–5.16]), risk of training injuries (RR = 3.75 [95% CI 1.59–8.83], p = 0.001), risk of competition injuries (RR = 1.79 [95% CI 0.65–4.90], p = 0.25) and overall concussion risk (RR = 10.04 [95% CI 0.91–110.46], p = 0.02) were greater in females. Ten sailors accounted for 17 illnesses. Females had a 3.33 increase in training and competition illnesses (IRR = 3.33 [95% CI 0.94–11.81]). Conclusions: Competition injury incidence was higher than previous reported sailing studies. Knee injuries were most prevalent and direct impacts caused most injuries. Female sailors reported a higher injury and illness incidence. These results may guide injury prevention efforts and the development of an IOC-equivalent consensus statement. Future studies should examine time loss. Full article

As the core space for students’ daily living and learning, the quality of the indoor wind environment and air quality in dormitory buildings is particularly critical. However, existing studies often neglect natural ventilation optimization under local climatic conditions and the multidimensional evaluation of health benefits, leaving notable gaps in dormitory design. Under the Healthy China Initiative, the indoor wind environment in university dormitories directly impacts students’ health and learning efficiency. This study selects dormitory buildings in Xuzhou as the research object and employs ANSYS FLUENT 2020 software for computational fluid dynamics (CFD) simulations, combined with orthogonal experimental design methods, to systematically investigate and optimize the indoor wind environment with a focus on healthy ventilation standards. The evaluation focused on three key metrics—comfortable wind speed ratio, air age, and CO₂ concentration—considering the effects of building orientation, corridor width, and window geometry, and identifying the optimal parameter combination. After optimization based on the orthogonal experimental design, the proportion of comfortable wind speed zones increased to 44.6%, the mean air age decreased to 258 s, and CO₂ concentration stabilized at 613 ppm. These results demonstrate that the proposed optimization framework can effectively enhance indoor air renewal and pollutant removal, thereby improving both air quality and the health-related performance of dormitory spaces. The novelty of this study lies in integrating regional climate conditions with a coordinated CFD–orthogonal design approach. This enables precise optimization of dormitory ventilation performance and provides locally tailored, actionable evidence for advancing healthy campus design. Full article

Wind power forecasting remains a major challenge for renewable energy integration, as conventional models often perform poorly when confronted with complex atmospheric dynamics. This study addresses the problem by developing a Spectral-Attentive Spatio-Temporal Graph Convolutional Network (SA-STGCN) designed to capture the intricate temporal and spatial dependencies of wind systems. The approach first applies wavelet transform decomposition to separate volatile wind signals into distinct frequency components, enabling more interpretable representation of rapidly changing conditions. A dynamic temporal attention mechanism is then employed to adaptively identify historical patterns that are most relevant for prediction, moving beyond the fixed temporal windows used in many existing methods. In addition, spectral graph convolution is conducted in the frequency domain to capture farm-wide spatial correlations, thereby modeling long-range atmospheric interactions that conventional localized methods overlook. Although this design increases computational complexity, it proves critical for representing wind variability. Evaluation on real-world datasets demonstrates that SA-STGCN achieves substantial accuracy improvements, with a mean absolute error of 1.52 and a root mean square error of 2.31. These results suggest that embracing more expressive architectures can yield reliable forecasting performance, supporting the stable integration of wind power into modern energy systems. Full article

Wind turbine blade damage detection is crucial for advancing wind energy as a sustainable alternative to fossil fuels. Existing methods based on image processing technologies face challenges such as limited adaptability to complex environments, trade-offs between model accuracy and computational efficiency, and inadequate real-time inference capabilities. In response to these limitations, we put forward MSWindD-YOLO, a lightweight real-time detection model for wind turbine blade damage. Building upon YOLOv5s, our work introduces three key improvements: (1) the replacement of the Focus module with the Stem module to enhance computational efficiency and multi-scale feature fusion, integrating EfficientNetV2 structures for improved feature extraction and lightweight design, while retaining the SPPF module for multi-scale context awareness; (2) the substitution of the C3 module with the GBC3-FEA module to reduce computational redundancy, coupled with the incorporation of the CBAM attention mechanism at the neck network’s terminus to amplify critical features; and (3) the adoption of Shape-IoU loss function instead of CIoU loss function to facilitate faster model convergence and enhance localization accuracy. Evaluated on the Wind Turbine Blade Damage Visual Analysis Dataset (WTBDVA), MSWindD-YOLO achieves a precision of 95.9%, a recall of 96.3%, an mAP@0.5 of 93.7%, and an mAP@0.5:0.95 of 87.5%. With a compact size of 3.12 MB and 22.4 GFLOPs inference cost, it maintains high efficiency. After TensorRT acceleration on Jetson Orin NX, the model attains 43 FPS under FP16 quantization for real-time damage detection. Consequently, the proposed MSWindD-YOLO model not only elevates detection accuracy and inference efficiency but also achieves significant model compression. Its deployment-compatible performance in edge environments fulfills stringent industrial demands, ultimately advancing sustainable wind energy operations through lightweight lifecycle maintenance solutions for wind farms. Full article

Floating vertical−axis wind turbines present unique advantages for deep−water offshore deployments, but their basin model testing encounters significant challenges in aerodynamic load simulation due to Reynolds scaling effects. While Froude−scaled experiments accurately replicate hydrodynamic behaviors, the drastic reduction in Reynolds numbers at the model scale leads to substantial discrepancies in aerodynamic forces compared to full−scale conditions. This study proposed two methodologies to address these challenges. Fully physical model tests adopt a “physical wind field + rotor model + floating foundation” approach, realistically simulating aerodynamic loads during rotor rotation. Semi−physical model tests employ a “numerical wind field + rotor model + physical floating foundation” configuration, where theoretical aerodynamic loads are obtained through numerical calculations and then reproduced using controllable actuator structures. For fully physical model tests, a blade reconstruction framework integrated airfoil optimization, chord length adjustments, and twist angle modifications through Taylor expansion−based sensitivity analysis. The method achieved thrust coefficient similarity across the operational tip−speed ratio range. For semi−physical tests, a cruciform−arranged rotor system with eight dynamically controlled rotors and constrained thrust allocation algorithms enabled the simultaneous reproduction of periodic streamwise/crosswind thrusts and vertical−axis torque. Numerical case studies demonstrated that the system effectively simulates six−degree−of−freedom aerodynamic loads under turbulent conditions while maintaining thrust variation rates below 9.3% between adjacent time steps. These solutions addressed VAWTs’ distinct aerodynamic complexities, including azimuth−dependent Reynolds number fluctuations and multidirectional force coupling, which conventional methods fail to accommodate. The developed techniques enhanced the fidelity of floating VAWT basin tests, providing critical experimental validation tools for emerging offshore wind technologies. Full article

Partial Discharge (PD) measurement is one of the effective methods for assessing the internal insulation condition of power transformers in factories and substations. The pulse current signals generated by PD within transformer windings are significantly influenced by the winding structure during their propagation from the discharge source to the external measurement system. This influence may lead to misinterpretation of the insulation status, particularly in the analysis of PD measurement results. Such effects are closely related to the signal transmission path and distance and exhibit a strong correlation with the winding transfer function, manifesting as attenuation, distortion, or delay of the measured signals compared to the original PD waveforms. Therefore, it is essential to investigate the impact of the discharge path on the propagation characteristics of transformer windings and its effect on PD waveforms. This paper establishes a simplified distributed parameter model of a 180-turn single-winding multi-conductor transmission line using the finite element method and mathematical modeling, deriving the transfer functions between the winding head or winding end and various internal discharge positions. By injecting different types of PD waveforms collected in the laboratory at various discharge locations within the winding, the alterations of PD signals propagated to the winding head and winding end are simulated, and clustering analysis is performed on the propagated PD signals of different types. Full article

A large number of practical systems show pronounced fractional-order features. In comparison with integer-order calculus, fractional-order calculus has been demonstrated to possess enhanced precision in the description of the dynamic behavior of complex systems. The increase in control accuracy and flexibility results from this improvement. This study explores a direct-drive wind power generation system featuring permanent magnets, which incorporates fractional-order direct current bus (DC-bus) capacitor and fractional-order inductor–capacitor–inductor (FOLCL) grid-connected filter. For the machine-side rectifier, a fractional-order sliding mode (FOSM) speed outer-loop control and a fractional-order proportional–integral (FOPI) current inner-loop control were designed. A voltage outer-loop control using FOSM and a current inner-loop control using FOPI were developed for the grid-side inverter. Through simulation analyses under various wind speeds and grid fault conditions, it is demonstrated that compared to a control strategy using FOPI controllers in both inner and outer loops, the proposed control scheme which employs a FOSM outer-loop and reduces the overshoot of DC-bus voltage and grid-connected current by 21.51% and 32.49%, respectively, under sudden wind speed changes. Furthermore, during grid voltage sag faults, the maximum drop in DC-bus voltage and grid-connected active power are reduced by 65.38% and 33.38%, respectively. These results highlight the proposed method’s superior dynamic and static performance, as well as enhanced resistance to disturbances. Full article

When exposed to high contact pressure and shear conditions, the sliding and/or rolling contact interfaces of moving mechanical systems can experience significant friction and wear losses, thereby impairing their efficiency, reliability, and environmental sustainability. Traditionally, these losses have been minimized using high-performance solid and liquid lubricants or surface engineering techniques like physical and chemical vapor deposition. However, increasingly harsh operating conditions of more advanced mechanical systems (including wind turbines, space mechanisms, electric vehicle drivetrains, etc.) render such traditional methods less effective or impractical over the long term. Looking ahead, an emerging and complementary solution could be tribocatalysis, a process that spontaneously triggers the formation of nanocarbon-based tribofilms in situ and on demand at lubricated interfaces, significantly reducing friction and wear even without the use of high-performance additives. These films often comprise a wide range of amorphous or disordered carbons, crystalline graphite, graphene, nano-onions, nanotubes, and other carbon nanostructures known for their outstanding friction and wear properties under the most demanding tribological conditions. This review highlights recent advances in understanding the underlying mechanisms involved in forming these carbon-based tribofilms, along with their potential applications in real-world mechanical systems. These examples underscore the scientific significance and industrial potential of tribocatalysis in further enhancing the efficiency, reliability, and environmental sustainability of future mechanical systems. Full article

Under extreme snowfall conditions, wind-induced snow drifting can lead to the redistribution of snow accumulation on roofs, resulting in localized overloads that pose a serious threat to building structural safety. Notably, morphological differences in snow particles significantly alter their aerodynamic characteristics, causing variations in their motion trajectories and increasing the uncertainty in determining roof snow loads. Therefore, this study develops a numerical simulation method that accounts for snow morphologies based on the drag coefficients of typical snow crystals, and further investigates the accumulation characteristics of differently shaped snow particles on typical roofs. Analysis results demonstrate that the observed variations in snow particle motion characteristics primarily originate from differences in their respective drag coefficients. The drag coefficient exerts a direct influence on particle settling velocity, which subsequently governs spatial distribution patterns of snow concentration and final accumulation patterns. Under identical inflow snow concentration conditions, particles with higher drag coefficients exhibit reduced depositional accumulation on roof surfaces. Notably, this shape-dependent effect diminishes with increasing roof span and slope. Full article

This paper presents a structured strategy for integrating the Sustainable Development Goals (SDGs) into university courses by linking them to competencies and learning outcomes. The proposed methodology, based on fuzzy logic, evaluates the degree of alignment between teaching activities and selected SDGs through matrices that connect competencies with assessment activities and expected learning outcomes, improving the gap regarding the inclusion of the SDGs and their articulation in terms of competencies. The approach was applied to two subjects from the Master’s Degree in Renewable Energy and Energy Efficiency at the Distance University of Madrid: “Electricity Market” and “Wind Energy”. In both cases, the learning outcomes were redesigned, and the activities were adjusted to ensure meaningful incorporation of sustainability principles into the curriculum. The method enables quantification of each activity’s contribution to the SDGs and supports a critical review of curriculum design to ensure coherent integration. The results indicate that project-based activities show the highest alignment with the SDGs, particularly with Goals 7, and 12, which achieve an average rating of 0.7 (high). The developed tool provides a practical and replicable solution for sustainability-oriented curriculum planning and can be adapted to other disciplines and educational programs. Full article

This paper proposes a 2D semi-analytical model based on the subdomain method for the performance analysis of a brushless doubly fed reluctance machine (BDFRM) with a salient pole rotor. In particular, assuming an infinite magnetic permeability of the iron core and assuming a smooth stator, the field calculation region is divided into two solution subdomains, i.e., the rotor slot and air-gap. The magnetic vector potential in each subdomain is obtained by solving the governing PDE by the separation of variables method and employing the boundary conditions between adjacent interfaces. Moreover, based on the stored magnetic energy in the air-gap, the calculation of the three-phase windings’ self and mutual inductances is presented. Through a case study involving a 6/2 pole BDFRM, the accuracy of the developed subdomain model is confirmed by comparing its analytically predicted results with those obtained from two-dimensional finite element method (FEM) simulations. Full article