Search Results (44)

The increasing penetration of wind and photovoltaic power intensifies power fluctuations and raises the requirement for reserve capacity allocation in hydro-wind-solar (HWS) systems. To address this issue, this study proposes a two-stage optimization framework for coordinated reserve configuration. In the first stage, the entropy weight method is used to evaluate heterogeneous reserve resources according to unit capacity cost, response time, and carbon emission intensity, thereby determining their response priority and obtaining an initial reserve allocation. In the second stage, alternative preference coefficient ratios for economy, rapidity, and low-carbon performance are assessed, and the resulting allocation proportions are fed back to the first stage to form a closed-loop optimization process. To solve the model, an improved Osprey Optimization Algorithm incorporating a Lens Imaging Opposition-Based Learning mechanism is adopted. A case study based on the Wudongde regional grid shows that the 2:1:2 preference-ratio scenario provides the best overall trade-off among the tested cases, with a reserve cost of 18,640.38 CNY (Chinese Yuan), carbon emissions of 8718.30 kg CO₂, and a response time of 4336.7 s. Compared with representative benchmark models, the proposed method achieves lower carbon emissions and faster response while maintaining competitive economic performance. The results demonstrate that the proposed framework can improve reserve allocation quality and operational adaptability in HWS systems with high renewable penetration. Full article

Characterizing both the CO₂ distribution and wind dynamics in the Martian mesosphere and lower thermosphere is vital for planetary atmospheric science and mission planning. In this work, we propose a novel dual-channel passive limb-viewing imaging system designed to simultaneously observe partial CO₂ column density and line-of-sight (LOS) wind speed from ultraviolet and visible airglow emissions under dayside and terminator illumination conditions. A dichroic beam splitter separates the ultraviolet and visible channels, ensuring high optical throughput and independent optimization of both subsystems. The ultraviolet channel targets O(¹S) 297.2 nm emission, a well-established Martian limb emission driven by CO₂ photodissociation under solar Lyman-α flux. By applying narrow-band imaging and brightness inversion, this channel provides quantitative constraints on CO₂ column density with a stable and well-defined response function. In the visible channel, we introduce a lens array-based compact static Michelson interferometer optimized for the O(¹S) 557.7 nm green line emission, which has been observed in the Martian dayside limb, providing Doppler wind measurements in the 60–180 km altitude range. Radiative transfer simulations using Mars Climate Database indicate retrieval precisions of ±6~8% for CO₂ column density and better than ±5 m/s for wind speed within the primary emission layer (approximately 60–160 km) under representative dayside limb conditions. This dual-parameter remote sensing concept simultaneously constrains the composition and dynamics of the Martian mesosphere and lower thermosphere region, addressing a long-standing observational gap. The compact and modular design of the system makes it well suited for future Mars orbiter payloads under nominal dayside and terminator observation geometries, providing critical data for validating global circulation models and supporting future entry, descent, and landing system design. Full article

As one of the payloads on board the Solar wind Magnetosphere Ionosphere Link Explorer (SMILE) spacecraft, the ultraviolet imager (UVI) aims to capture N2 Lyman–Birge–Hopfield (LBH) aurora continuously on a high-eccentricity orbit. The UVI instrument includes an intensified charge-coupled device (ICCD) for far ultraviolet (FUV) wavelength. It comprises a sealed image intensifier, a relay lens system, a CCD, and a mechanical housing. ICCD’s performance characteristics are evaluated before integrating with the optical system of the UVI, including the quantum efficiency, radiant gain, background characteristics, excess noise factor, image quality, and signal-to-noise ratio (SNR). The testing procedure and results are presented and discussed. The results demonstrate that the comprehensive performance of the detector is good, and provide critical technical support for quantitative applications. Full article

Aratus’ poem Phaenomena, and particularly its second part commonly known as Diosemeia (Signs from Zeus), offers a compelling blend of poetic narrative and proto-scientific observation. Composed in the 3rd century B.C., the work reflects the Hellenistic interest in systematizing knowledge of the natural world through both literary and empirical means. Within its verses, meteorological phenomena such as clouds, rain, hail, winds, and atmospheric changes are not merely described but interpreted through a cosmological lens that reflects the worldview of the era. Aratus Solensis employs a poetic language that transforms everyday weather into a meaningful sequence of signs tied to divine order and celestial cycles providing in that way a kind of classified weather prognostics. Full article

This study presents an innovative pipeline for processing, compressing, and remotely visualizing large-scale numerical simulations of fluid dynamics in a virtual wind tunnel (VWT), leveraging virtual and augmented reality (VR/AR) for enhanced analysis and high-end visualization. The workflow addresses the challenges of handling massive databases generated using Direct Numerical Simulation (DNS) while maintaining visual fidelity and ensuring efficient rendering for user interaction. Fully immersive visualization of supersonic (Mach number 2.86) spatially developing turbulent boundary layers (SDTBLs) over strong concave and convex curvatures was achieved. The comprehensive DNS data provides insights on the transport phenomena inside turbulent boundary layers under strong deceleration or an Adverse Pressure Gradient (APG) caused by concave walls as well as strong acceleration or a Favorable Pressure Gradient (FPG) caused by convex walls under different wall thermal conditions (i.e., Cold, Adiabatic, and Hot walls). The process begins with a .vts file input from a DNS, which is visualized using ParaView software. These visualizations, representing different fluid behaviors based on a DNS with a high spatial/temporal resolution and employing millions of “numerical sensors”, are treated as individual time frames and exported in GL Transmission Format (GLTF), which is a widely used open-source file format designed for efficient transmission and loading of 3D scenes. To support the workflow, optimized Extract–Transform–Load (ETL) techniques were implemented for high-throughput data handling. Conversion of exported Graphics Library Transmission Format (GLTF) files into Graphics Library Transmission Format Binary files (typically referred to as GLB) reduced the storage by 25% and improved the load latency by 60%. This research uses Unity’s Profile Analyzer and Memory Profiler to identify performance limitations during contour rendering, focusing on the GPU and CPU efficiency. Further, immersive VR/AR analytics are achieved by connecting the processed outputs to Unity engine software and Microsoft HoloLens Gen 2 via Azure Remote Rendering cloud services, enabling real-time exploration of fluid behavior in mixed-reality environments. This pipeline constitutes a significant advancement in the scientific visualization of fluid dynamics, particularly when applied to datasets comprising hundreds of high-resolution frames. Moreover, the methodologies and insights gleaned from this approach are highly transferable, offering potential applications across various other scientific and engineering disciplines. Full article

In light of the United Nations Sustainable Development Goals (SDGs), particularly Goal 5 (Gender Equality) and Goal 13 (Climate Action), integrating gender dimensions into climate adaptation strategies can foster more inclusive and equitable development pathways. While China’s rapid expansion of wind power has been a central component of its climate action strategy, gender considerations in energy policies remain largely overlooked. This study utilizes data from 31 provinces from 2008 to 2021 to assess the impact of wind power Feed-in tariff (FIT) adjustment policy in 2014 on female employment in China. A difference-in-differences (DID) approach is employed using a continuous treatment variable. Due to data availability, we focus on urban unit employment, which reflects mainly formal employment. The results show that FIT subsidy reduction in 2014 substantially reduced female employment at the 1% level, while men were not impacted. The underlying mechanism is validated by observing a significant decline in overall wages and that only female employment in the service sector was notably affected. Wage reduction likely leads to a decrease in demand for service-oriented products, a sector where women dominate, thus amplifying the gendered impact. By providing empirical evidence and theoretical insights, this study highlights the gendered effects of energy policy as part of climate change mitigation efforts and underscores the need to align Goal 5 with Goal 13 through more inclusive and gender-sensitive energy policy design. Full article

The possibility of charging and possibly discharging electric cars can influence not only the balancing of power demand profiles in the grid and the stabilization of voltage profiles but also the appropriate management of electricity within the grid of an industrial plant equipped with its own RES resources. For this purpose, the concept of “power supply modes” can be introduced, which involves intelligent demand-side management. Each technological process in an industrial plant should be assigned a specific level of importance and priority. These priorities can be numbered according to their importance (weights) and marked with appropriate colors. One thus obtains a qualitative assessment of energy consumption within the plant (demand side) through the lens of power modes. With respect to the ability to charge electric vehicles within the plant grid, such priorities can also be assigned to individual charging options. If a given RES has sufficient generation capacity during a particular time period, the cost of charging is low. However, if the RESs are not operational during a given period (e.g., nighttime in the case of photovoltaics or during calm weather in the case of wind turbines), vehicles can still be charged but according to a different priority, which, of course, involves higher costs. By having access to data on the generation capacity of distributed RESs and knowing the preferences of employees, including the number of electric cars and the expected periods of vehicle charging, it is possible to predict the degree of use of available green energy and manage it efficiently. The analyses presented in the article represent an original approach to the flexibility of operation not only of the electricity grid but also of the internal energy system of industrial plants. It offers a novel perspective aimed at maximizing the share of RESs in the overall energy balance and minimizing the costs associated with the operation of RESs. The theoretical opportunity of sustainable sharing with employees a dedicated charging mode named “free charging”, powered by RESs, could represent an appropriate solution for CO₂ emission reduction within Scope 3, Category 3, “employee commuting”, according to the GHG Protocol requirements. The original methodology proposed in the article aligns with activities related to the energy transition. Full article

In modern autonomous systems, measurement repeatability and precision are crucial for robust decision-making algorithms. Stereovision, which is widely used in safety applications, provides information about an object’s shape, orientation, and 3D localisation. The camera’s lens distortion is a common source of systematic measurement errors, which can be estimated and then eliminated or at least reduced using a suitable correction/calibration method. In this study, a set of cameras equipped with Basler lenses (C125-0618-5M F1.8 f6mm) and Sony IMX477R matrices are calibrated using a state-of-the-art Zhang–Duda–Frese method. The resulting distortion coefficients are used to correct the images. The calibrations are evaluated with the aid of two novel methods for lens distortion measurement. The first one is based on linear regression with images of a vertical and horizontal line pattern. Based on the evaluation tests, outlying cameras are eliminated from the test set by applying the 2$\sigma$ criterion. For the remaining cameras, the MSE was reduced up to 75.4 times, to 1.8 px−6.9 px. The second method is designed to evaluate the impact of lens distortion on stereovision applied to bird tracking around wind farms. A bird’s flight trajectory is synthetically generated to estimate changes in disparity and distance before and after calibration. The method shows that at the margins of the image, lens distortion might introduce errors into the object’s distance measurement of +17%−+20% for cameras with the same distortion and from −41% up to $+\infty$ for camera pairs with different lens distortions. These results highlight the importance of having well-calibrated cameras in systems that require precision, such as stereovision bird tracking in bird–turbine collision risk assessment systems. Full article

In this study, we investigated the impacts of typhoons on the transformation of anticyclonic eddies (AEs) into subsurface anticyclonic eddies (SAEs) in the northwestern subtropical Pacific Ocean (NWSP) based on an ocean reanalysis product and multiple satellite observations. Results suggest that while the heavy precipitation and strong positive wind stress curl (WSC) induced by the passage of typhoons may be two main driving factors that transformed shallow mixed layer depth (MLD) AEs (i.e., those shallower than 50 m at the eddy core) into SAEs, the latter played a greater role in such transformation. In addition, shallow MLD AEs with a less depressed isopycnal structure near the eddy center before the passage of typhoons were more likely to be transformed into SAEs under the impacts of typhoons. The likely timing of such transformation may be within 9 days after the passage of typhoons. For deep MLD AEs (i.e., those deeper than 80 m at the eddy core), the impacts of typhoons may be much less prominent below the mixed layer. Based on a diagnostic analysis of the vertical potential vorticity (PV) flux at the surface, we examined the mechanism and dynamic processes involved in the transformation of deep MLD AEs into SAEs under the impacts of typhoons. Results show that while typhoons played a positive role in maintaining low PV within deep MLD AEs, which was favorable for further transformation into SAEs, the diabatic process associated with the net air–sea heat flux was the crucial favorable condition for the transformation of deep MLD AEs into SAEs. Full article

This paper presents the design and analysis of an efficient energy management system for a wind lens integrated with a permanent magnet synchronous generator (PMSG) and a zeta converter. The wind lens, a ring-shaped structure encircling the rotor, enhances the turbine’s capability to capture wind energy by increasing the wind influx through the turbine. In the contemporary wind energy sector, PMSGs are extensively employed due to their superior performance characteristics. This study integrates a 1 kW PMSG system with a wind lens to optimize power extraction from the wind energy conversion system (WECS) under varying wind speeds. A comparative analysis of different control strategies for maximum power point tracking (MPPT) is conducted, including the incremental conductance (INC) method and the perturb and observe (P&O) method. The performance of the MPPT controller integrated with the wind lens-based PMSG system is assessed based on output DC voltage and power delivered to the load. To evaluate the overall effectiveness of these control strategies, both steady-state voltage and dynamic response under diverse wind conditions are examined. The system is modeled and simulated using the MATLAB R2023a/Simulink 9.1 software, and the simulation results are validated to demonstrate the efficacy of the proposed energy management system. Full article

To address the global warming issue, China is prioritizing the development of clean energy sources such as wind and solar power under its “dual carbon target”. However, the expansion of these resources is constrained by their intermittency and the spatial and temporal distribution of wind and solar energy. This paper systematically reviews the evolution of wind and solar energy reserves, their development potential, and their current status in China from a geographical perspective. In conjunction with existing research, this paper anticipates future exploration in the realm of wind–solar complementary development or multi-energy complementary development, viewed through the lens of resource quantity. The anticipated findings are intended to furnish a theoretical foundation for further studies on the development and utilization of wind and solar energy resources within China. Full article

As renewable energy sources such as wind and photovoltaics continue to enter the grid, their intermittency and instability leads to an increasing demand for peaking and frequency regulation. An efficient dynamic monitoring method is necessary to improve the safety level of intelligent operation and maintenance of power stations. To overcome the insufficient detection accuracy and poor adaptability of traditional methods, a novel fault early warning method with careful consideration of dynamic characteristics and model optimization is proposed. A combined loss function is proposed based on the dynamic time warping and the mean square error from the perspective of both shape similarity and time similarity. A prediction model of steam turbine intermediate-stage extraction temperature based on the gate recurrent unit is then proposed, and the change in prediction residuals is utilized as a fault warning criterion. In order to further improve the diagnostic accuracy, a human evolutionary optimization algorithm with lens opposition-based learning is proposed for model parameter adaptive optimization. Experiments on real-world normal and faulty operational data demonstrate that the proposed method can improve the detection accuracy by an average of 1.31% and 1.03% compared to the long short-term memory network, convolutional neural network, back propagation network, extreme learning machines, gradient boosting decision tree, and LightGBM models. Full article

In an era focused on deepening green sustainable development, improving corporate ESG performance has become a theoretical focal point. Starting from the positional attributes of the interlocking director network, this study investigates the influence of a company’s position within this network on its ESG performance among China’s A-share-listed companies from 2009 to 2022. It utilizes Huazheng ESG ratings from the Wind database and employs regression models, analyses, endogeneity, and propensity score matching tests via Stata15.0 to probe the internal mechanisms at play. Research findings indicate that corporations at the core of the interlocking director network exhibit significantly better ESG performance compared to those in peripheral positions. The interlocking director network enhances corporate ESG performance by improving internal control levels. Media attention positively influences the effect of the interlocking director network on corporate ESG performance. Further analysis reveals that the beneficial impact of the interlocking director network on ESG performance is more pronounced in highly marketized corporations, those outside of heavy pollution industries, and those with a higher proportion of female directors. Economically, the positive effect of the interlocking director network on ESG performance enhances both earnings per share and total factor productivity. This study offers a novel pathway for enhancing corporate sustainability in emerging economies through the lens of the interlocking director network, drawing on China’s experience. It aims to guide emerging markets in fostering ESG practices among corporations, thus offering theoretical insights for enhancing ESG performance. Full article

The Onshore Wind Power All-DC Generation System (OWDCG) is designed to integrate with renewable energy sources by modifying the grid structure. This adaptation supports the grid infrastructure and addresses the challenges of large-scale wind power AC collection and harmonic resonance during transmission. Crucially, small disturbance stability parameters are essential for ensuring the system’s stable operation. Unlike conventional power systems, the OWDCG exhibits strong coupling between subsystems, accentuating the small disturbance stability issue due to the dynamic nature of its converter control system. The impedance method facilitates the decomposition of such systems into subsystems, offering insights into the destabilization mechanism through the lens of negative impedance contribution. This approach is conducive to conducting small disturbance stabilization analyses. To tackle this issue, the initial step involves deriving the input and output equivalent impedance models of the subsystem, considering the topological structure, control features, and operational dynamics of the OWDCG. Subsequently, the impact of circuit and control parameters on the system’s impedance characteristics and small-disturbance stability is examined through Bode diagrams and Nyquist curves. This analysis identifies critical parameters for small-disturbance stability, guiding the stable operation and parameter optimization of the OWDCG. The analysis highlights that the main control strategies for stability are the Modular Multilevel Converter (MMC) DC voltage control and the inner-loop current control gain. Validation of the theoretical findings is achieved through simulation results using PSCAD/EMTDC. Full article