This work presents an experimental investigation of a simple ejector-based passive hydrogen recirculation system for a 0.5 kW small-scale open-cathode proton exchange membrane fuel cell (PEMFC) stack. Several ejector geometries were designed and fabricated using a 3D printer, and the final configuration employed a converging nozzle with a diameter of 0.2 mm and a mixing-chamber-to-nozzle diameter ratio of 4.5. Experiments showed that the ejector achieves entrainment ratios peaking at ~1.3 at low current and stabilizing around 0.9–1.0 at higher loads, while maintaining stable operation across the full load range. Compared with a dead-ended anode configuration, passive recirculation reduces the total hydrogen supply required by the system, with the reduction being strongly influenced by purge dynamics that are prominent in sub-kW operation. Beyond averaged hydrogen saving, purge-event transients were quantified using time-resolved supply-flow traces and introduced purge-event metrics (overshoot amplitude and purge-induced excess volume) to capture purge-dominated behavior and the buffering role of recirculation. Finally, by contrasting without and with anode inlet pressure setting operations, this paper shows that pressure regulation can improve steady utilization yet partially compromise transient suppression, motivating purge-aware pressure control as a practical operational guideline for small-scale open-cathode PEMFC systems.

Low productivity remains a key limitation of conventional solar stills for desalination. In this study, we evaluated the performance of a solar still integrated with copper rods filled with nano-enhanced phase change material (NPCM), benchmarked against three configurations: a conventional still, a still with empty copper rods, and a still using unmodified phase change material (PCM). Four single-slope solar stills were fabricated and tested simultaneously under identical ambient conditions. Distillate yield, temperature profiles, and thermal efficiency were recorded during daytime (9:00–17:00) and nighttime operation to assess the influence of dispersed nanoparticles on heat storage and release behavior. The NPCM still achieved a distillate yield of 4.27 kg/m²·day, compared with 1.98 kg/m²·day for the conventional still. The improved thermal conductivity and heat retention of the nano-PCM matrix resulted in a 19.4% higher nocturnal yield (1.49 kg/m²·day) relative to the PCM still (1.28 kg/m²·day). Peak rod temperature reached 86 °C for the NPCM configuration, versus 79 °C (PCM) and 68 °C (empty rod). Thermal efficiency increased from 47.20% (conventional) to 70.15% (NPCM), representing a 65% gain in productivity and a 48.62% improvement in efficiency. These findings confirm that nanoparticle dispersion in PCM enhances heat storage capacity, thermal distribution, and freshwater yield in solar stills. The NPCM-integrated design offers a promising route toward higher-efficiency, sustainable solar desalination for arid and coastal regions.

By integrating multiple superconducting magnetic energy storage units (SMESU), the multi-superconducting magnetic energy storage system (M-SMES) facilitates the capacity expansion and standardization of energy storage systems. However, during parallel operation, parameter and dynamic mismatches among units often cause uneven power sharing and circulating currents. To address this, an adaptive virtual synchronous generator (AVSG) control method was proposed to achieve stable operation. First, the power transfer characteristics of M-SMES and the circulating current characteristics arising from the cascaded converter structure were analyzed. Second, a coordinated control strategy for the cascaded converters was designed accordingly. The front-stage DC/DC chopper employs voltage-current dual-loop control to guarantee DC-link voltage stability, while the rear-stage DC/AC inverter adopts adaptive inertia and damping control to ensure efficient and stable power delivery, thereby achieving effective active power sharing and reducing active circulating currents. Subsequently, the virtual complex impedance was dynamically adjusted based on the reactive power deviation to accomplish reactive power sharing and suppress reactive circulating currents. Finally, simulation results of a three-unit parallel system on the Matlab/Simulink platform verify the superior performance of the proposed strategy in power sharing and circulating current suppression.

Co-located battery energy storage (BESS) is often sized as a single power and energy rating for electric-vehicle fast-charging stations (EVCSs), although feeder adequacy is governed by different limits. This paper separated five requirements on a single backward/forward-sweep (BFS) model: branch-loading relief, residual voltage support, power conversion system (PCS) apparent-power capability, storage energy, and post-stress recharge. Active power was sized against branch-loading alone; voltage was then restored through unity-power-factor correction and local capacitive support. On the IEEE 33-bus benchmark, two placements and four demand levels produced a nominal branch-loading-relief requirement of 0 to 855.56 kW, yet three of eight cases required no active storage while remaining voltage-infeasible. Exhaustive enumeration of 720 processing orders yielded 0.07% to 96.69% sequential excess. Independent tests with two published current-limit parameterizations showed strong capacity-data dependence: a 275/120 A set left only two cases requiring 20.25 and 158.53 kW, whereas a multi-tier set admitted no current-feasible active-only solution. Unity-power-factor correction was insufficient in all eight nominal cases, leaving 114.77 to 879.94 kVAr of additional support and 0.32% to 96.17% conditional PCS headroom. For a 4-hour design duration, synchronous recharge ranged from the 4.43 h active-rating/efficiency floor to 31.19 h under voltage limitation, while branch-loading never bound. A single MW/MWh rating therefore cannot represent all five adequacy requirements.

Wind energy is an abundant and sustainable renewable resource, yet its stochastic and low-frequency characteristics pose significant challenges for efficient utilization. Triboelectric nanogenerators (TENGs) have emerged as a promising technology for harvesting ambient wind energy, owing to their lightweight structures, low startup wind speeds, and excellent adaptability to irregular airflow conditions. Over the past decade, wind-driven TENGs have undergone rapid development, evolving from simple energy harvesters into multifunctional platforms capable of efficient energy conversion and self-powered sensing. Consequently, a timely review of this rapidly advancing field is highly desirable. This review provides a systematic overview of recent advances in wind-driven TENGs, covering their fundamental mechanisms, structural evolution, and emerging applications. The development of wind-driven TENGs from fluttering and rotary architectures to advanced direct-current systems is summarized, with key strategies for improving energy harvesting and output performance. Emerging applications in sustainable energy harvesting and self-powered sensing are highlighted, demonstrating the growing potential of wind-driven TENGs for energy utilization and environmental perception. Finally, future opportunities and challenges are discussed, including higher-efficiency energy harvesting, intelligent self-powered sensing, and integrated autonomous systems. This review aims to provide insights into future developments of wind-driven TENGs toward sustainable energy technologies and intelligent self-powered infrastructures.

The power-hydrogen-methanol multi-energy coupling system enables flexible conversion of electricity, hydrogen, and liquid chemical energy, providing an effective pathway for renewable energy accommodation and low-carbon operation. However, spatial mismatch between renewable-energy-rich regions and load centers, together with wind and photovoltaic fluctuations, brings challenges to cross-regional energy coordination, flexible regulation, and economic operation. To address these issues, this paper proposed an optimal scheduling method for a power-hydrogen-methanol multi-energy coupling system considering cross-regional methanol transportation. First, a coupled operation framework was established for the sending-end and receiving-end regions, where transmission tie-lines and methanol transportation jointly form dual cross-regional energy transfer pathways. Second, a methanol storage and transportation model considering transportation delay was developed. By integrating electrolytic hydrogen production, methanol synthesis, methanol reforming, and methanol fuel cell power generation, the coordinated operation of the methanol production-storage-transportation-utilization chain and the power-hydrogen system is realized. Furthermore, a unified multi-timescale scheduling model was constructed to coordinate hourly power balance with daily methanol storage and transportation characteristics. On this basis, a reward-penalty differentiated stepped carbon trading scheme and a data-driven robust optimization (DDRO) approach are incorporated. Wind and photovoltaic uncertainty sets were built using historical forecasting errors, and the resulting two-stage robust scheduling model was solved by the column-and-constraint generation (C&CG) algorithm. Case studies on the IEEE 39-bus system showed that the proposed method achieves an annual operating cost of ¥381.275 billion, carbon emissions of 672,500 kt, and a worst-case load shedding rate of only 0.05%. These results confirm that the proposed approach can promote interregional renewable energy utilization, improve the hydrogen supply structure in the receiving-end region, and coordinate system economy, low-carbon performance, and supply reliability under renewable generation uncertainty.

The solar cell capacitance simulator in one dimension was used to examine how the perovskite layer’s properties influence devices’ performance in a simulated solar cell structure comprising graphene oxide (GO) as the hole transport material (HTL), tungsten trioxide (WO₃) as the electron transport material (ETL), and methylammonium lead iodide (MAPbI₃) as the absorber layer. The simulation investigated the effects of the MAPbI₃ layer’s thickness, defect density, electron affinity, and doping concentration on photovoltaic parameters. The baseline nonoptimized structure yielded a power conversion efficiency (PCE) of 7.1%, with a short-circuit current density (Jsc) of 11.38 mA/cm², an open-circuit voltage (Voc) of 0.80 V, and a fill factor (FF) of 77.9%. Optimization of the MAPbI₃ layer’s thickness to 1.2 µm and the acceptor doping density to 1.0 × 10²² cm^-3 improved the PCE to 22.9%, with Jsc = 28 mA/cm², Voc = 0.93 V, and FF = 87.4%. These improvements stem from enhanced light absorption and more efficient charge separation. Alternating current (AC) analysis through capacitance–voltage and electrochemical impedance spectroscopy indicated that optimized doping reduces series resistance and modifies the depletion region’s width, though the interpretation of the Nyquist plots requires careful consideration of competing transport and recombination processes. These findings provide guidance for experimental design of perovskite solar cells, though the simulated efficiencies represent theoretical upper bounds that may not be achievable experimentally with these transport layer materials.

As digital grid development in Guangdong Province advances, the accumulation of multi-source heterogeneous data and the low efficiency of fault disposition in distribution networks have become increasingly prominent issues. To facilitate the effective use of multi-source heterogeneous data and efficient decision-making for distribution network fault disposition, this paper proposes a method for constructing a fault disposition knowledge graph based on multi-source heterogeneous data. First, the characteristics of multi-source heterogeneous data in distribution networks were analyzed, and a framework for constructing a fault disposition knowledge graph was designed accordingly. Then, named entities were extracted from unstructured fault texts using EBERT-BiLSTM-CRF. Based on the recognized entities, BiLSTM-GA was used to identify semantic relations and generate knowledge triples. Finally, fault data from a distribution network in a specific region of Guangdong Province were used in a case study, and the resulting knowledge graph was visualized and managed using the GridGraph graph database. Within the proposed knowledge graph construction framework, the complete BiLSTM-CRF-GA extraction configuration achieved a mean precision of 91.16%, a mean recall of 92.94%, and a mean F1-score of 92.06% across five matched data splits, supporting its effectiveness in extracting fault-disposition knowledge from multi-source data.

Hydrogen energy, distinguished by its high energy density, superior combustion calorific value, and environmental benignity, represents a highly promising low carbon energy carrier for the 21st century energy transition and serves as a critical technological pillar supporting global energy restructuring and the attainment of carbon peaking and carbon neutrality objectives. In this paper, we systematically reviewed the current landscape and core technological bottlenecks of the hydrogen industry, structured along its three fundamental value chain segments: hydrogen production, storage and transportation, and end use applications. Our findings indicated that water electrolysis constitutes a pivotal route for green and sustainable hydrogen generation. Moreover, alkaline water electrolysis attained a technology readiness level (TRL) of 9 and exhibited a hydrogen storage efficiency of approximately 60%–75%. Nevertheless, the intrinsic intermittency and fluctuations inherent in wind and solar power generation tended to induce performance degradation and shortened the operational lifespan of electrolysis units, thereby critically undermining the stability and economic viability of green hydrogen production. With respect to storage and transportation, the dominant high pressure gaseous hydrogen technology likewise reached TRL 9; however, it was constrained by a relatively low volumetric storage density (20–40 kg/m³) and notable safety concerns. Liquid hydrogen storage offered a substantially higher volumetric density, exceeding 60 kg/m³, albeit at the expense of considerable energy consumption and elevated costs during liquefaction and transportation. In contrast, solid state hydrogen storage combined enhanced safety with high volumetric densities in the range of 50–110 kg/m³, rendering it a primary focus of research and development efforts. In terms of applications, hydrogen was predominantly deployed in the transportation sector, industrial decarbonization of steelmaking and chemical production, and hydrogen based energy storage and power generation.

The integration of renewable energy sources (RESs) and electric vehicles (EVs) in grid-connected microgrids offers significant potential for improving energy flexibility, renewable-energy utilization, and supply reliability. However, many existing studies assume continuous EV availability or full user participation, which may overestimate the actual flexibility provided by EV fleets. To address this limitation, this study proposes a unified behavior-aware framework for a grid-connected photovoltaic–wind turbine–battery energy storage system electric vehicle (PV-WT-BESS-EV) microgrid, combining quokka swarm optimization (QSO) for optimal component sizing with a rule-based energy management system (RB-EMS). The framework incorporates EV availability, state-of-charge constraints, user willingness, mobility patterns, V2G/G2V operation, and time-of-use pricing. The system was evaluated over 8760 h using measured 2024 meteorological data and the actual hourly load profile of Al-Ramadi General Teaching Hospital, Iraq. Results showed that incorporating driver behavior reduces both V2G and G2V energy exchange by 50.88%, while battery discharge and charging increase by 1.47% and 1.48%, respectively. Grid import increases by only 0.52%, whereas exported energy decreases by 3.41%, and the cost of energy increases by 1.78%, while maintaining LPSP = 0. Optimal sizing changes from 116 WT, 1331 PV, and 937 battery units to 98 WT, 1335 PV, and 958 battery units. Statistical comparison over five independent runs showed that QSO achieves the lowest mean fitness and standard deviation, outperforming PSO, POA, and GA in convergence consistency and robustness. Sensitivity analysis further confirmed the robustness of the proposed framework under variations in EV fleet size, electricity pricing, and user behavioral composition. Increased EV penetration enhances V2G/G2V energy exchange, while tariff and behavioral variations primarily affect grid interaction and EV flexibility without compromising system reliability. Overall, the proposed framework provides a realistic and robust approach for jointly evaluating microgrid sizing and operation under practical EV behavioral constraints.

The electrification of vehicles has been considered as one of the possible alternatives to minimize the dependence on fossil fuel and environmental emissions in smart cities. Although there has been increase in the uptake of electric vehicles (EV) in cities its widespread adoption is impacted by different challenges such as limited battery range, high purchase costs, and improved charging convenience. To address these challenges, an innovative technology is proposed termed as dynamic wireless charging technology (DWCT), which is a type of electric road systems (ERS) infrastructure that allows for the propulsion and charging of EV. DWCT helps to charge the EV while in motion. Although previous research has covered the technical aspects of DWCT, the widespread deployment of DWCT in smart cities is limited by different barriers. Hence, there is a gap in the current research regarding institutional and social perspective regarding the barriers that influence DWCT based ERS adoption. Therefore, this article examines the environmental, social, institutional, economic, and technological barriers that impact the adoption of dynamic wireless electric transfer technologies for charging EV in smart cities. Findings from this study further investigate the feasibility of DWCT by identifying recommendations to support road electrification towards the deployment of ERS in smart cities.

The thermal performance of solar air heater (SAH) is the standard for evaluating SAH. To enhance the thermal performance of SAH, we proposed the novel configuration incorporating the sinusoidal corrugated absorb plate. The thermal characteristics of sinusoidal-corrugated SAH were systematically investigated using the combined approach of numerical simulation and theoretical analysis. First, comparative study with conventional triangular-corrugated SAH was conducted, demonstrating the superior comprehensive performance of the sinusoidal plate in enhancing heat transfer while mitigating flow resistance. Second, the effects of key geometric parameters of the sinusoidal corrugation (wavelength and wave height) on the collector efficiency and pressure drop were thoroughly analyzed, leading to the identification of optimized parameter range. Furthermore, the double-layer sinusoidal-corrugated SAH model was developed to explore its synergistic heat transfer enhancement mechanism. The results indicated that the sinusoidal corrugation effectively disrupted the thermal boundary layer and induced secondary flows, which has higher heat collection efficiency and lower pressure drop and heat dissipation coefficient. The optimal wavelength was 20 mm, and the optimal wave height was 15 mm, the maximum heat collection efficiency was 61.58%, and the minimum heat dissipation coefficient was 4.66 W/m·K. The double-layer structure further enhanced the heat output. Based on simulated data, the high-precision fitting relationship ( R² > 0.98) was established between the heat collection efficiency and inlet air Reynolds number ( Re). This study provides theoretical basis and data support for the design and optimization of high-efficiency SAH.