Wind power’s intermittent nature presents challenges for grid integration, while hydrogen production via electrolysis offers potential solutions for both energy storage and clean transportation fuel. This study conducted a comprehensive technoeconomic assessment of integrated wind‐powered electrolysis systems with compressed hydrogen storage to determine optimal configurations and economic viability. Five system configurations were modeled, combining direct wind‐to‐electrolysis coupling and grid‐connected operation with varying storage capacities. Technical performance was simulated using actual wind data from three geographic locations, while economic analysis employed discounted cash flow methodology, examining multiple revenue streams. Direct‐coupled systems achieved 62.4% average efficiency from wind to hydrogen, while grid‐connected systems reached 68.7%. The hybrid configuration demonstrated superior economic performance, achieving levelized hydrogen costs as low as $3.39/kg in favorable locations. Grid balancing services reduced production costs by 13.8% for hybrid systems. Carbon abatement costs ranged from $46.3 to 142.7/ton CO 2 eq without incentives, decreasing to $5.8–58.2/ton with enhanced policy support. The results indicate that wind‐powered electrolysis systems can achieve economic viability in specific markets when implementing revenue stacking strategies. Geographic location significantly impacts performance, with the wind capacity factor being more influential than peak wind speeds. Policy incentives remain critical for near‐term deployment, though projected cost reductions suggest competitive hydrogen production without subsidies is achievable by 2030.

Voltage inconsistency is one of the important factors that cause safety problems in power batteries. Therefore, based on electric vehicle operation data from the automotive enterprise monitoring platform, this paper builds upon the Principal Component Analysis (PCA) method and incorporates Discrete Wavelet Transform (DWT) characterized by possesses multi‐resolution analysis and time‐frequency localization characteristics to achieve data denoising and feature extraction, thereby proposing a fault identification method for power battery cell voltage inconsistency based on DWT and PCA. First, according to the change of false alarm rate (FAR), the voltage data of 20 rounds of charge‐discharge cycles is selected as the dataset for model threshold training, which solves the problem of FAR fluctuation caused by early voltage oscillation. Second, the influence of different wavelet functions on the diagnostic results of this method is investigated, and it is found that db4 wavelet can eliminate the FAR caused by noise. Finally, the method is used to analyze the three vehicles randomly selected from the monitoring platform of automobile enterprises which have voltage inconsistency alarms. The results show that for voltage inconsistency faults of the same vehicle model, the method can detect the faults 2 days earlier than the platform; for voltage inconsistency faults of gradual and transient type occurring in different vehicles, the method can detect the faults 9 days and 22 min earlier than the platform; for voltage inconsistency faults occurring in multiple units in the same vehicle, the method can also combine the anomaly rate to rank the degree of faults of the single cell. Based on the primary performance metrics reported in the literature and algorithmic principles, we find that, compared with current mainstream methods, the proposed approach outperforms them in accuracy, precision, recall, and computational time. The research findings significantly enhance the efficiency of power battery fault identification.

This study investigated the feasibility of quantitative real‐time polymerase chain reaction (qPCR) as a monitoring and decision‐making support tool for high‐rate continuous biohydrogen production. Three identical lab‐scale dynamic membrane (DM) bioreactors were operated under operational disturbances, and the microbial dynamics were monitored using qPCR analysis of major bacterial strains, including Clostridium pasteurianum and Streptococcus equinus , alongside the universal bacterial primer. Despite a similar performance and metabolic flux of hydrogen production after the disturbance, the qPCR copy numbers of target strains showed significant differences. When the normalized abundance of C. pasteurianum to the universal primer was no less than 2.6 copies/copies, the process performance eventually recovered, whereas the performance deteriorated when the normalized abundance of C. pasteurianum was lower than 2.6 copies/copies. The increased abundance of S. equinus was also associated with the deterioration of process performance. These results suggest that qPCR monitoring of key strains is a useful decision‐making tool for continuous biohydrogen production.

The adoption of photovoltaic (PV) technology for energy generation is expanding rapidly, yet performance losses caused by environmental factors such as dust accumulation and rainfall remain significant challenges. This paper introduces a novel and comprehensive model for predicting the power output of PV panels by integrating three distinct sub‐models: one for estimating hourly dust accumulation, another for predicting dust removal during rainfall events, and a third for calculating the resulting power output. Unlike previous studies, this model precisely accounts for the dual impact of dust deposition and rainfall cleaning, which has often been oversimplified or neglected. Using 1464 h of meteorological data (61 days), the model demonstrates that rainfall can significantly reduce accumulated dust, thereby mitigating power losses. Specifically, 23 h of light to moderate rainfall removed approximately 57% of the dust, decreasing power losses from 8.82% to 3.6%. Furthermore, the model highlights that light rainfall, even with minimal dust accumulation, can still reduce performance—an aspect rarely considered in past research. This model provides a valuable tool for better predicting PV panel performance under varying environmental conditions, offering significant implications for PV system operation and maintenance, particularly in dust‐prone areas.

The burgeoning demand for power across the globe and the disastrous effect of climate change that results from power generation through depleting unclean fuel sources have necessitated the use of renewable and clean fuels. Hydrogen is a good alternative but only when produced from low‐carbon energy resources. However, hydrogen production via this pathway has a high cost and low system efficiency. Therefore, a comparative cost analysis has been performed for hydrogen production through solar power tower (SPT) and parabolic trough collector (PTC) with proton exchange membrane (PEM) electrolyzer. This is carried out using different cycle configurations comprising a modified steam Rankine cycle (MSRC), supercritical carbon dioxide Brayton cycle (SCBC), and organic Rankine cycle (ORC). Optimization of the solar tower power configurations is also performed for improved system performance. The result of the analysis showed that all SPT’s configurations outperformed the PTC’s configurations except for the configuration comprising the steam Rankine cycle (SRC) and ORC due to how well it performed under the low operating temperature of the PTC system. The levelized cost of hydrogen (LCOH) ranged from 7.78 $/kg for the PTC‐MSRC‐ORC configuration to 17.76 $/kg for the PTC‐MSRC‐SCBC configuration. The parametric analysis of the system also showed that the capacity factor had the greatest influence on system performance. Furthermore, a multiobjective optimization of the system using a brute‐force algorithm for minimizing the LCOH and maximizing efficiency improved the system performance in all configurations.

Conventional physics‐based fuel cell models have faced limitation in explaining the through‐plane liquid water distributions observed by state‐of‐the‐art imaging techniques. To elucidate these experimental findings, we advance a temperature‐dependent phase separation model (TDPSM) framework by introducing separate liquid transport equations for each porous constituent. The proposed theoretical framework incorporates relative hydrophobicity at overlapping interfaces and employs a volume‐averaging scheme to reveal the physics underlying optical liquid visualization. A novel validation approach is proposed, enabling simultaneous prediction of through‐plane liquid profiles and conventional polarization curves with strong agreement to experimental data. Extensive numerical simulations comparing water transport scenarios with and without a microporous layer (MPL) integrate previously fragmented experimental findings on the MPL’s dual role. The study also presents water management strategies for two operating regimes: (i) low‐temperature high‐humidity (LTHH), where liquid flooding dominates, and (ii) high‐temperature low‐humidity (HTLH), where membrane dehydration presents an emerging industrial challenge. Under LTHH conditions, a hydrophobicity order of catalyst layer (CL) > MPL > gas diffusion layer (GDL) establishes an interfacial liquid pump that enables effective liquid removal. In contrast, under HTLH operation, a more hydrophobic MPL relative to the CL (MPL > CL) forms an interfacial barrier that sustains reliable membrane water retention. Overall, this theoretical framework redefines water management as a synergistic outcome of relative hydrophobic characteristics between adjacent porous layers, rather than as properties of isolated components.

Against the backdrop of imbalanced urban–rural spatial structures and energy resource allocation, along with the continuous increase in distributed photovoltaic (PV) penetration rate, achieving orderly PV expansion and optimal energy storage (ES) configuration has become an urgent requirement for urban–rural distribution network planning. Existing research generally overlooks regional differences between urban and rural areas, making multiregional collaborative optimization difficult to achieve. Therefore, this paper proposes a distributed collaborative planning model for PV and ES (PV–ES) in multiregional urban–rural distribution networks based on the analytical target cascading (ATC) algorithm. By establishing a collaborative planning model that accounts for urban–rural differences, system decoupling is achieved through decomposition modeling and distributed parallel solution is accomplished using the ATC algorithm. Case validation demonstrates that the proposed model can coordinately optimize PV–ES configuration across multiple urban–rural regions, simultaneously enhancing system economics and significantly reducing impact on the upper‐level grid.The study further proposes a three‐level planning implementation pathway of “municipal–county–township” transmission, providing systematic technical methods and planning support for promoting the integration of urban–rural energy infrastructure.

This research presents a novel approach by combining magnetohydrodynamic (MHD) flow with ohmic heating to investigate the conjugate mixed convective transport of ferrofluid in a discretely heated, smooth/wavy‐walled, square‐shaped porous compartment featuring a clockwise spinning cylindrical body positioned at various locations. It aims to maximize heat transfer efficiency and minimize entropy production. Numerical solutions are obtained using the Galerkin finite element weighted residual method to solve the two‐dimensional Navier–Stokes and heat energy equations. The parametric variations include Grashof number (10 6 ≤ Gr ≤ 10 8 ), Reynolds number (10 3 ≤ Re ≤ 10 4 ), and Hartmann number (31.62 ≤ Ha ≤ 100), dimensionless cylinder diameter (0.2 ≤ D ≤ 0.4), dimensionless cylinder vertical position (0.25 ≤ Y c ≤ 0.75), and dimensionless heater strip size (0.25 ≤ d h ≤ 0.75). The results are quantitatively expressed through the Nusselt number ( Nu ) of the hot wall, the mean fluid temperature, the overall entropy production, and the thermal performance criterion ( TPC ). Extensive analysis reveals that a transition from a conduction‐dominated region to a convection‐dominated region occurs at Gr = 3 × 10 7 , Re = 5477.23, and Ha = 74. Notably, the maximum values of Gr , Re , and Ha at d h = 0.25, D = 0.2, and Y c = 0.75 result in a 36.84% increase in the Nusselt number and a 64.89% reduction in TPC compared to those at d h = 0.75, thereby indicating optimal conditions. In contrast, the largest heater size yields the poorest performance, with a 26.93% drop in Nu and a 265.22% increase in TPC . Insights into the MHD mixed convective flow with a ferrofluid‐filled copper powder porous medium within a corrugated cavity at higher Grashof numbers contribute to a novel and deeper understanding of velocity and temperature distributions, heat transfer, and irreversibility, which mimics a nuclear reactor fuel channel and fluid‐chilling blankets.

This research focuses on improving solar cell efficiency and environmental sustainability by introducing a new type of tandem perovskite solar cell (PSC) that uses Ca 3 NBr 3 and Ca 3 NCl 3 as two active absorbing layers. The design was simulated using SCAPS‐1D software and includes an fluorine‐doped tin oxide (FTO) base layer, CdS as the electron transport layer (ETL), V 2 O 5 as the hole transport layer (HTL), and carefully selected absorber materials. The study closely examines how factors like absorber thickness, defect levels, and doping concentrations affect the device’s overall performance. The best‐performing model, with 500 nm thick absorbers and low interface defects, reached an impressive efficiency of 35.76%, a current density of 35.06 mA/cm 2 , a voltage of 1.23 V, and a fill factor (FF) of 83.18%. The impact of temperature and electrical resistance was also analyzed, showing that low series resistance and stable temperature conditions are essential for high performance. These results highlight the strong potential of Ca 3 NBr 3 /Ca 3 NCl 3 based tandem solar cells as a promising and lead‐free solution for the next generation of high‐efficiency photovoltaic (PV) devices.

Copper zinc tin sulfide (CZTS) is an earth‐abundant, nontoxic, and cost‐effective absorber material that has gained significant attention as a sustainable alternative to CIGS and CdTe in thin‐film photovoltaics (PVs). With a direct bandgap of 1.4–1.5 eV and a high absorption coefficient exceeding 10 4 cm −1 , CZTS is well suited for both single‐junction and tandem solar cell architectures. Recent advancements have raised the power conversion efficiency (PCE) of single‐junction CZTSSe devices to approximately 12.6%, while tandem configurations combining CZTS with silicon or perovskite subcells have achieved simulated or experimental efficiencies exceeding 25%. Despite these promising developments, performance is still constrained by intrinsic defects, secondary phase formation, unfavorable band alignment, and severe open‐circuit voltage ( V OC ) deficits that limit carrier collection. This review provides a comprehensive analysis of the structural, optical, and electronic properties of CZTS thin‐films, fabrication and synthesis routes, and the design principles of tandem and multijunction architecture. Furthermore, it summarizes recent progress in defect passivation, interface engineering, and device integration, and outlines future research directions toward scalable, stable, and high‐efficiency CZTS–based PV technologies.