Search Results (302)

Energy policies and economies of scale have promoted the expansion of renewable energy sources, leading to the displacement of conventional generation units and a consequent reduction in system inertia. Low inertia amplifies frequency deviations in response to generation–load imbalances, increasing the risk of load shedding and service interruptions. To address this issue, this paper proposes a coordinated control strategy based on neuro-fuzzy networks, applied to a hybrid energy storage system (HESS) composed of batteries and supercapacitors. The controller is designed to simultaneously emulate virtual inertia and implement virtual droop control, thereby improving frequency stability and reducing reliance on spinning reserve. Additionally, a state-of-charge (SOC) management layer is integrated to prevent battery operation in critical zones, mitigating degradation and extending battery lifespan. The neuro-fuzzy controller dynamically coordinates the power exchange both among the energy storage technologies (batteries and supercapacitors) and between the HESS and the conventional generation unit, enabling a smooth and efficient transition in response to power imbalances. The proposed strategy was validated through simulations in MATLAB R2022b using a two-area power system model with parameters sourced from the literature and validated references. System performance was evaluated using standard frequency response metrics, including performance indicators (ITSE, ISE, ITAE and IAE) and the frequency nadir, demonstrating the effectiveness of the approach in enhancing frequency regulation and ensuring the operational safety of the energy storage system. Full article

This study simulates an open-cavity random distributed Raman amplifier for optimal performance across a 5 THz S-band spectrum (196.2–201.1 THz; 1490.76–1527.99 nm), evaluating its capacity via a 50-channel WDM grid with 100 GHz spacing. The primary Raman pump wavelength was tuned from 1318 to 1344 nm to identify the optimal point. A Fiber Bragg Grating (FBG), placed at the end of a 60 km single-mode fiber and upshifted 88 nm from the pump, enhances efficiency by transferring energy to the amplified signal, minimizing power variation. Results yield < 2 dB gain ripple across channels using raw Raman amplification without flattening filters with minor degradation from residual channels, confirming the DRA design’s viability for high-density S-band optical communication expansion. Full article

This study investigates a dynamic switching method for signal relay protocols in Cooperative Pattern Division Multiple Access (Co-PDMA) networks. The proposed approach aims to fully utilize the advantages of signal relays in fading-prone environment while simultaneously reducing the network outage probability and improving the throughput and energy efficiency. To demonstrate the necessity of implementing the dynamic switching method for signal relay protocols, Co-PDMA networks with Decode-and-Forward (DF) or Amplify-and-Forward (AF) protocols are explored over Nakagami-m fading. Based on the analysis of these two scenarios, the overall outage probability, throughput, and energy efficiency of the Co-PDMA network with a dynamic DF/AF protocol are determined. The results demonstrate that the proposed method selects the optimal signal relay protocol for forwarding user data in a simple and efficient manner across varying transmit signal-to-noise ratios, quality of service, and signal relay locations. Compared with fixed signal relay protocols, the proposed method is more conducive to achieving green communication in Co-PDMA networks, as it enhances communication reliability and the total volume of data transmitted. Full article

Background/Objectives: Nanobubble water (NBW) is being studied increasingly for its potential benefits in sports nutrition. This study aimed to evaluate whether supplementation with ozone-enriched NBW (O₃-NBW) could improve integrated exercise capacity—encompassing endurance performance, muscle strength, and postexercise recovery as well as body composition and metabolic adaptations in mice. Methods: Male ICR mice (n = 24) were allocated into Control, Air-NBW, or O₃-NBW (0.2–1 mg/L ozone) groups for 4 weeks. Results: O₃-NBW treatment considerably enhanced forelimb grip strength and treadmill running endurance compared to the Control group (both p < 0.05). Analyses of body composition revealed a higher proportion of lean mass and muscle glycogen storage in NBW groups, notably with O₃-NBW. Serum markers gathered post-exercise demonstrated a reduction in ammonia and blood urea nitrogen (BUN), suggesting improved nitrogen metabolism. Levels of resting serum creatine kinase (CK) and uric acid were also lower in O₃-NBW mice, indicating potential benefits for muscle recovery. In addition, O₃-NBW treatment significantly enhanced oxygen consumption (VO₂) and reduced the respiratory quotient (RQ), signifying amplified fat oxidation, while also lowering total energy expenditure (all p < 0.05). Spontaneous wheel-running activity remained consistent across all the groups. Conclusions: Taken as a whole, these findings emphasize that O₃-NBW supplementation offers ergogenic and metabolic advantages by improving integrated exercise capacity and efficiency of gas exchange, without adverse effects. Full article

This paper examines the interconnection and wavelet coherence between the green cryptocurrency market and the green conventional market, utilizing daily data. The research period covers 1 July 2020 to 30 September 2024. Employing the time-varying parametric vector autoregression (TVP-VAR) model and wavelet coherence analysis, we capture both short- and long-term spillovers across markets. The results show that cryptocurrencies, particularly Binance and Litecoin, act as dominant transmitters of volatility and return shocks, while green conventional indices function mainly as receivers with strong self-dependence. Spillover intensity is highly time-varying, with peaks during periods of systemic stress, particularly during the COVID-19 pandemic, and troughs indicating diversification opportunities. These findings advance the literature on systemic risk and portfolio design by showing that crypto assets can simultaneously amplify vulnerabilities and enhance diversification when combined with green finance instruments. For policy, the results highlight the need for regulatory frameworks that integrate sustainability taxonomies, mandate environmental disclosures for digital assets, and incentivize energy-efficient blockchain adoption to align crypto markets with sustainable finance objectives. This research enhances our understanding of the interrelationship between green investments and cryptocurrencies, providing valuable insights for investors and policymakers on risk management and diversification strategies in an increasingly sustainable financial landscape. Full article

This study investigates the impact of different duct designs on the energy-harvesting performance of oscillating-wing systems in both partially and fully confined environments. Numerical simulations were conducted to examine the effects of straight, convergent–straight, and convergent–divergent duct configurations on the aerodynamic forces and overall energy extraction efficiency. Under partial confinement, the convergent–divergent duct demonstrated a significant improvement of 67.5% in power output over the ductless baseline configuration. This enhancement is attributed to the increased incoming flow velocity and amplified pressure difference around the wing, which improve the effectiveness of energy generation. However, the straight and convergent–straight ducts reduced the harvester’s performance due to the diminished flow velocity within each duct. Under full confinement, all duct configurations substantially enhanced energy-harvesting performance, with the convergent–straight duct providing the highest efficiency gain (84.9%). This improvement is primarily due to the increased velocity and pressure differential across the wing surfaces, which maximise the heaving force and overall energy generation performance. These findings highlight the critical role of duct geometry in optimising energy-harvesting performance, both in partially confined and fully confined flow environments. Full article

This study addresses this gap by proposing a multilevel fuzzy evaluation model combined with an analytic hierarchy process (AHP) to quantify the greenness of furniture products across their entire lifecycle. Focusing on an office desk as a case study, we developed an indicator system encompassing environmental attributes, resource efficiency, energy consumption, economic costs, and quality performance. Weighting results revealed that environmental attributes (27.2%) and resource efficiency (27.2%) dominated the greenness evaluation, with material recycling rate (33.5%) and solid waste pollution (24.3%) as critical sub-indicators. The prototype achieved a moderate greenness score of 70.38/100, highlighting optimization potential in renewable material adoption (10% current rate) and modular design for disassembly. Mechanically recycled materials could reduce lifecycle emissions by 18–25% in key categories. The model demonstrates scalability for diverse furniture types and informs policy-making by prioritizing high-impact areas such as toxic material reduction and energy-efficient manufacturing, thus amplifying its global and interdisciplinary multiplier effects. Full article

Environmental innovation represents a pivotal pathway toward achieving energy efficiency improvements, carbon footprint reduction, and ecological sustainability enhancement. The research investigates Chinese manufacturing enterprises listed on domestic stock exchanges throughout 2011–2023. The analytical framework utilizes count-based regression methodologies to explore how R&D investment intensity influences eco-innovation capabilities. Results demonstrate curvilinear associations linking R&D expenditure levels with both substantive and strategic environmental innovation achievements across industrial firms. This outcome successfully passed the turning-point test. Environmental oversight and financial incentives produce divergent moderating influences on innovation trajectories. Regulatory frameworks generate restrictive impacts through narrowing optimal investment ranges and dampening peak innovation outputs, whereas fiscal support mechanisms foster expansive effects via broadening resource availability and amplifying achievement levels. Cross-sectional examination uncovers substantial variations among ownership categories and geographical locations. State-owned enterprises demonstrate significantly lower optimal R&D intensity thresholds. Private firms require substantially elevated thresholds for optimal performance. Inland territories manifest unbalanced innovation dynamics. Coastal areas exhibit symmetric innovation patterns. The research enriches empirical knowledge in eco-innovation studies while offering context-specific strategic insights. The findings establish theoretical foundations and practical guidance for policy architects designing integrated environmental management systems that enhance innovation capabilities. Full article

The consistent quality control of ultrapure water (UPW) in semiconductor manufacturing depends on removing trace organonitrogen compounds such as urea. Due to its high solubility, chemical stability, and neutral polarity, urea is inadequately removed by conventional processes. Even at low concentrations, it elevates total organic carbon (TOC) and reduces electrical resistivity. The use of reclaimed water as a sustainable feed stream amplifies this challenge because its nitrogen content is variable and persistent. Conventional methods such as reverse osmosis, ultraviolet oxidation, and ion exchange remain limited in treating urea due to its uncharged, low-molecular-weight nature. This review examines the performance and limitations of these processes and explores electrochemical oxidation (EO) as an alternative. Advances in EO are analyzed with attention to degradation pathways, electrode design, reaction selectivity, and operational parameters. Integrated systems combining EO with membrane filtration, adsorption, or chemical oxidation are also reviewed. Although EO shows promise for selectively degrading urea, its application in UPW production is still in its early stages. Challenges such as low conductivity, byproduct formation, and energy efficiency must be addressed. The paper first discusses urea in reclaimed water and associated removal challenges, then examines both conventional and emerging treatment technologies. Subsequent sections delve into the mechanisms and optimization of EO, including electrode materials and operational parameters. The review concludes with a summary of main findings and a discussion of future research directions, aiming to provide a comprehensive foundation for validating EO as a viable technology for producing UPW from reclaimed water. Full article

Decarbonization of the Greek economy requires significant investments in clean technologies. This will boost demand for goods and services and will create multiplier effects on output value added and employment, though reliance on imported technologies might increase the trade deficit. This study employs input–output analysis to estimate the direct, indirect, and multiplier effects of green transition investments on Greek output, value added, employment, and imports across five-year intervals from 2025 to 2050. Two scenarios are considered: the former is based on the National Energy and Climate Plan (NECP), driven by a large-scale exploitation of RES and technologies promoting electrification of final demand, while the latter (developed in the context of the CLEVER project) prioritizes energy sufficiency and efficiency interventions to reduce final energy demand. In the NECP scenario, GDP increases by 3–10% (relative to 2023), and employment increases by 4–11%. The CLEVER scenario yields smaller direct effects—owing to lower investment levels—but larger induced impacts, since energy savings boost household disposable income. The consideration of three sub-scenarios adopting different levels of import-substitution rates in key manufacturing sectors exhibits pronounced divergence, indicating that targeted industrial policies can significantly amplify the domestic economic benefits of the green transition. Full article

In recent years, growing concerns over environmental degradation and deepening awareness of the necessity of sustainable development have propelled green and low-carbon energy transition into a focal issue for both academia and policymakers. By decomposing energy transition into the transformation of energy structure and the upgrading of energy efficiency, this study investigates the impact and mechanisms of green finance on energy transition across 30 provinces (municipalities and autonomous regions) in China, with the exception of Tibet. In addition, the impact of climate change is incorporated into the analytical framework. Empirical results demonstrate that green finance development significantly accelerates energy transition, a conclusion robust to rigorous validation. Analysis of the mechanism shows that green finance promotes energy transition through the facilitation of technological innovation and the upgrade of industrial structures. Moreover, empirical evidence reveals that climate change undermines the promotional influence of sustainable finance on energy system transformation. The magnitude of this suppression varies nonlinearly across provincial jurisdictions with differing energy transition progress. Regional heterogeneity analyses further uncover marked discrepancies in climate–finance interactions, demonstrating amplified effects in coastal economic hubs, underdeveloped western provinces, and regions with mature eco-financial markets. According to these findings, actionable policy suggestions are put forward to strengthen green finance and accelerate energy transition. Full article

This study presents a breakthrough in sustainable injection molding by uniquely combining a backpropagation neural network (BPNN) with particle swarm optimization (PSO) to overcome traditional optimization challenges. The BPNN’s exceptional ability to learn complex nonlinear relationships between six key process parameters (including melt temperature and holding pressure) and product quality is amplified by PSO’s intelligent search capability, which efficiently navigates the high-dimensional parameter space. Together, this hybrid approach achieves what neither method could accomplish alone: the BPNN accurately models the intricate process-quality relationships, while PSO rapidly converges on optimal parameter sets that simultaneously meet strict quality targets (66–70 g weight, 3–5 mm thickness) and minimize energy consumption. The significance of this integration is demonstrated through three key outcomes: First, the BPNN-PSO combination reduced optimization time by 40% compared to traditional trial-and-error methods. Second, it achieved remarkable prediction accuracy (RMSE 0.8229 for thickness, 1.5123 for weight) that surpassed standalone BPNN implementations. Third, the method’s efficiency enabled SMEs to achieve CAE-level precision without expensive software, reducing setup costs by approximately 25%. Experimental validation confirmed that the optimized parameters decreased energy use by 28% and material waste by 35% while consistently producing parts within specifications. This research provides manufacturers with a practical, scalable solution that transforms injection molding from an experience-dependent craft to a data-driven science. The BPNN-PSO framework not only delivers superior technical results but does so in a way that is accessible to resource-constrained manufacturers, marking a significant step toward sustainable, intelligent production systems. For SMEs, this framework offers a practical pathway to achieve both economic and environmental sustainability, reducing reliance on resource-intensive CAE tools while cutting production costs by an estimated 22% through waste and energy savings. The study provides a replicable blueprint for implementing data-driven sustainability in injection molding operations without compromising product quality or operational efficiency. Full article

Bird-dropping fouling and hotspot anomalies remain the most prevalent and detrimental defects in utility-scale photovoltaic (PV) plants; their co-occurrence on a single module markedly curbs energy yield and accelerates irreversible cell degradation. However, markedly disparate visual–thermal signatures of the two phenomena impede high-fidelity concurrent detection in existing robotic inspection systems, while stringent onboard compute budgets also preclude the adoption of bulky detectors. To resolve this accuracy–efficiency trade-off for dual-defect detection, we present YOLOv8-SG, a lightweight yet powerful framework engineered for mobile PV inspectors. First, a rigorously curated multi-modal dataset—RGB for stains and long-wave infrared for hotspots—is assembled to enforce robust cross-domain representation learning. Second, the HSV color space is leveraged to disentangle chromatic and luminance cues, thereby stabilizing appearance variations across sensors. Third, a single-head self-attention (SHSA) block is embedded in the backbone to harvest long-range dependencies at negligible parameter cost, while a global context (GC) module is grafted onto the detection head to amplify fine-grained semantic cues. Finally, an auxiliary bounding box refinement term is appended to the loss to hasten convergence and tighten localization. Extensive field experiments demonstrate that YOLOv8-SG attains 86.8% mAP@0.5, surpassing the vanilla YOLOv8 by 2.7 pp while trimming 12.6% of parameters (18.8 MB). Grad-CAM saliency maps corroborate that the model’s attention consistently coincides with defect regions, underscoring its interpretability. The proposed method, therefore, furnishes PV operators with a practical low-latency solution for concurrent bird-dropping and hotspot surveillance. Full article

With their superior switching speed, GaN high-electron-mobility transistors (HEMTs) enable high power density, reduce energy losses, and increase power efficiency in a wide range of applications, such as power electronics, due to their high breakdown voltage. GaN-HEMT devices are subject to long-term reliability due to the self-heating effect and lattice mismatch between the SiC substrate and the GaN. Depletion-mode GaN HEMTs are utilized for radio frequency applications, and this work investigates three wide-bandgap (WBG) GaN HEMT fixed-frequency oscillators with output buffers. The first GaN-on-SiC HEMT oscillator consists of an HEMT amplifier with an LC feedback network. With the supply voltage of 0.8 V, the single-ended GaN oscillator can generate a signal at 8.85 GHz, and it also supplies output power of 2.4 dBm with a buffer supply of 3.0 V. At 1 MHz frequency offset from the carrier, the phase noise is −124.8 dBc/Hz, and the figure of merit (FOM) of the oscillator is −199.8 dBc/Hz. After the previous study, the hot-carrier stressed RF performance of the GaN oscillator is studied, and the oscillator was subject to a drain supply of 8 V for a stressing step time equal to 30 min and measured at the supply voltage of 0.8 V after the step operation for performance benchmark. Stress study indicates the power oscillator with buffer is a good structure for a reliable structure by operating the oscillator core at low supply and the buffer at high supply. The second balanced oscillator can generate a differential signal. The feedback filter consists of a left-handed transmission-line LC network by cascading three unit cells. At a 1 MHz frequency offset from the carrier of 3.818 GHz, the phase noise is −131.73 dBc/Hz, and the FOM of the 2nd oscillator is −188.4 dBc/Hz. High supply voltage operation shows phase noise degradation. The third GaN cross-coupled VCO uses 8-shaped inductors. The VCO uses a pair of drain inductors to improve the Q-factor of the LC tank, and it uses 8-shaped inductors for magnetic coupling noise suppression. At the VCO-core supply of 1.3 V and high buffer supply, the FOM at 6.397 GHz is −190.09 dBc/Hz. This work enhances the design techniques for reliable GaN HEMT oscillators and knowledge to design high-performance circuits. Full article

Heating, ventilation, and air-conditioning (HVAC) systems account for the largest share of energy consumption in European Union (EU) buildings, representing approximately 40% of the final energy use and contributing significantly to carbon emissions. Latent thermal energy storage (LTES) using phase change materials (PCMs) has emerged as a promising strategy to enhance HVAC efficiency. This review systematically examines the role of latent thermal energy storage using phase change materials (PCMs) in optimizing HVAC performance to align with EU climate targets, including the Energy Performance of Buildings Directive (EPBD) and the Energy Efficiency Directive (EED). By analyzing advancements in PCM-enhanced HVAC systems across residential and commercial sectors, this study identifies critical pathways for reducing energy demand, enhancing grid flexibility, and accelerating the transition to nearly zero-energy buildings (NZEBs). The review categorizes PCM technologies into organic, inorganic, and eutectic systems, evaluating their integration into thermal storage tanks, airside free cooling units, heat pumps, and building envelopes. Empirical data from case studies demonstrate consistent energy savings of 10–30% and peak load reductions of 20–50%, with Mediterranean climates achieving superior cooling load management through paraffin-based PCMs (melting range: 18–28 °C) compared to continental regions. Policy-driven initiatives, such as Germany’s renewable integration mandates for public buildings, are shown to amplify PCM adoption rates by 40% compared to regions lacking regulatory incentives. Despite these benefits, barriers persist, including fragmented EU standards, life cycle cost uncertainties, and insufficient training. This work bridges critical gaps between PCM research and EU policy implementation, offering a roadmap for scalable deployment. By contextualizing technical improvement within regulatory and economic landscapes, the review provides strategic recommendations to achieve the EU’s 2030 emissions reduction targets and 2050 climate neutrality goals. Full article