China, People’s Republic

This paper presents an improved Equivalent Consumption Minimization Strategy (ECMS) designed to optimize energy management for the hybrid hydrogen fuel power setups in multirotor drones. The proposed strategy aims to reduce hydrogen consumption and enhance the performance of the system consisting of Proton Exchange Membrane Fuel Cells (PEMFCs) and lithium batteries. Multirotor drones experience rapid power fluctuations due to their agile maneuvering but PEMFCs are unable to meet these demands swiftly due to their inherent limitations. To address this lithium batteries supplement peak power requirements and absorb excess energy on the DC bus. However this can lead to energy loss if the batteries are charged when not required. Our improved ECMS considers these inefficiencies and adjusts energy distribution to reduce hydrogen consumption and optimize the system’s performance. The proposed strategy effectively maintains the lithium batteries’ State of Charge (SOC) reduces hydrogen usage and enhances overall system efficiency when compared to traditional ECMS approaches.

Biogas (primarily biomethane) as a carbon-neutral renewable energy source holds great potential to replace fossil fuels for sustainable hydrogen production. Conventional biogas reforming systems adopt strategies similar to industrial natural gas reforming posing challenges such as high temperatures high energy consumption and high system complexity. In this study we propose a novel multi-product sequential separation-enhanced reforming method for biogas-derived hydrogen production which achieves high H2 yield and CO2 capture under mid-temperature conditions. The effects of reaction temperature steam-to-methane ratio and CO2/CH4 molar ratio on key performance metrics including biomethane conversion and hydrogen production are investigated. At a moderate reforming temperature of 425 ◦C and pressure of 0.1 MPa the conversion rate of CH4 in biogas reaches 97.1% the high-purity hydrogen production attains 2.15 mol-H2/mol-feed and the hydrogen yield is 90.1%. Additionally the first-law energy conversion efficiency from biogas to hydrogen reaches 65.6% which is 11 percentage points higher than that of conventional biogas reforming methods. The yield of captured CO2 reaches 1.88 kg-CO2/m3 -feed effectively achieving near-complete recovery of green CO2 from biogas. The mild reaction conditions allow for a flexible integration with industrial waste heat or a wide selection of other renewable energy sources (e.g. solar heat) facilitating distributed and carbonnegative hydrogen production.

Effective water management is crucial for the optimal performance and durability of proton exchange membrane fuel cells (PEMFCs) in automotive applications. Conventional techniques like electrochemical impedance spectroscopy (EIS) face challenges in accurately measuring high-frequency resistance (HFR) impedance during dynamic vehicle operations. This study proposes a novel stack water management stability control and vehicle energy control method to address these limitations. Simulation and experimental results demonstrate improved system and powertrain efficiency extended stack lifespan and optimized hydrogen consumption. These findings contribute to advancing robust water management strategies supporting the transition toward sustainable zero-emission fuel cell vehicles.

Against the backdrop of ever‑increasing energy demand and growing awareness of en‑ vironmental protection the research and optimization of hydrogen‑related multi‑energy systems have become a key and hot issue due to their zero‑carbon and clean characteristics. In the scheduling of such multi‑energy systems a typical problem is how to describe and deal with the uncertainties of multiple types of energy. Scenario‑based methods and ro‑ bust optimization methods are the two most widely used methods. The first one combines probability to describe uncertainties with typical scenarios and the second one essentially selects the worst scenario in the uncertainty set to characterize uncertainties. The selection of these scenarios is essentially a trade‑off between the economy and robustness of the so‑ lution. In this paper to achieve a better balance between economy and robustness while avoiding the complex min‑max structure in robust optimization we leverage artificial in‑ telligence (AI) technology to generate enough scenarios from which economic scenarios and feasible scenarios are screened out. While applying a simple single‑layer framework of scenario‑based methods it also achieves both economy and robustness. Specifically first a Transformer architecture is used to predict uncertainty realizations. Then a Gener‑ ative Adversarial Network (GAN) is employed to generate enough uncertainty scenarios satisfying the actual operation. Finally based on the forecast data the economic scenar‑ ios and feasible scenarios are sequentially screened out from the large number of gener‑ ated scenarios and a balance between economy and robustness is maintained. On this ba‑ sis a multi‑energy collaborative optimization method is proposed for a hydrogen‑based multi‑energy microgrid with consideration of the coupling relationships between energy sources. The effectiveness of this method has been fully verified through numerical exper‑ iments. Data show that on the premise of ensuring scheduling feasibility the economic cost of the proposed method is 0.67% higher than that of the method considering only eco‑ nomic scenarios. It not only has a certain degree of robustness but also possesses good economic performance.

N-type sulfide semiconductors are promising photocatalysts due to their broad visible-light absorption facile synthesis and chemical diversity. However photocorrosion and limited electron transport in one-step excitation and solid-state Z-scheme systems hinder efficient overall water splitting. Liquidphase Z-schemes offer a viable alternative but sluggish mediator kinetics and interfacial side reactions impede their construction. Here we report a stable Z-scheme system integrating n-type CdS and BiVO₄ with a [Fe(CN)₆]³⁻/[Fe(CN)₆]⁴⁻ mediator achieving 10.2% apparent quantum yield at 450 nm with stoichiometric H₂/O₂ evolution. High activity reflects synergies between Pt@CrOx and Co3O4 cocatalysts on CdS and cobalt-directed facet asymmetry in BiVO₄ resulting in matched kinetics for hydrogen and oxygen evolution in a reversible mediator solution. Stability is dramatically improved through coating CdS and BiVO4 with different oxides to inhibit Fe4[Fe(CN)6]3 precipitation and deactivation by a hitherto unrecognized mechanism. Separate hydrogen and oxygen production is also demonstrated in a twocompartment reactor under visible light and ambient conditions. This work unlocks the long-sought potential of n-type sulfides for efficient durable and safe solar-driven hydrogen production.

Aiming at resolving the problem of stable and efficient operation of integrated green hydrogen production storage and supply hydrogen refueling stations at different time scales this paper proposes a multi-time-scale hierarchical energy management strategy for integrated green hydrogen production storage and supply hydrogen refueling station (HFS). The proposed energy management strategy is divided into two layers. The upper layer uses the hourly time scale to optimize the operating power of HFS equipment with the goal of minimizing the typical daily operating cost and proposes a parameter adaptive particle swarm optimization (PSA-PSO) solution algorithm that introduces Gaussian disturbance and adaptively adjusts the learning factor inertia weight and disturbance step size of the algorithm. Compared with traditional optimization algorithms it can effectively improve the ability to search for the optimal solution. The lower layer uses the minute-level time scale to suppress the randomness of renewable energy power generation and hydrogen load consumption in the operation of HFS. A solution algorithm based on stochastic model predictive control (SMPC) is proposed. The Latin hypercube sampling (LHS) and simultaneous backward reduction methods are used to generate and reduce scenarios to obtain a set of high-probability random variable scenarios and bring them into the MPC to suppress the disturbance of random variables on the system operation. Finally real operation data of a HFS in southern China are used for example analysis. The results show that the proposed energy management strategy has a good control effect in different typical scenarios.

This study systematically investigates the fracture behavior of X80 pipeline steel welded joints under hydrogen-induced cracking (HIC) conditions through combined experimental characterization and numerical simulation. Microstructural observations and Vickers hardness testing reveal significant heterogeneity in the base metal heat-affected zone (HAZ) and weld metal (WM) resulting in spatially non-uniform mechanical properties. A userdefined subroutine (USDFLD) was employed to assign continuous material property distributions within the finite element model accurately capturing mechanical heterogeneity and its influence on crack-tip mechanical fields and crack propagation paths. Results show that welding thermal cycles induce pronounced microstructural evolution significantly altering hardness and strength distributions which in turn affect the evolution of crack-tip stress and plastic strain fields. Crack propagation preferentially occurs toward regions of higher yield strength where limited plasticity leads to intensified cracktip stress concentration accelerating crack growth and extending propagation paths. Moreover crack growth is accompanied by local unloading near the crack tip reducing peak stress and strain compared to the initial stationary crack tip. The stress and strain field reconfiguration are primarily localized near the crack tip while the far-field mechanical response remains largely stable.

Hydrogen gas is a promising clean-energy vector that can alleviate the current imbalance between energy supply and demand diversify the energy portfolio and underpin the sustainable development of oil and gas resources. This study pinpoints the factors that govern hydrogen quantification by pulsed-neutron logging. Monte Carlo simulations were performed to map the spatial distribution of capture γ-rays in formations saturated with either water or hydrogen and to systematically assess the effects of pore-fluid composition hydrogen density gas saturation lithology and borehole-fluid type. The results show that the counts of capture γ-rays are litter in hydrogen-bearing formations. For lowto moderate-porosity rocks the dynamic response window for hydrogensaturated pores is approximately 10% wider than that for methane-saturated pores. Increasing hydrogen density or decreasing gas saturation raises the capture-γ ratio while narrowing the dynamic range. Changes in borehole fluid substantially affect the capture-γ ratio yet have only a minor impact on the dynamic range. Lithology imposes an additional control: serpentinite enriched in structural water generates markedly higher capture-γ ratios that may complicate the quantitative evaluation of hydrogen.

Proliferation of co-located petrol-hydrogen fueling stations is an effective solution for widespread deployment of hydrogen as a transportation fuel. Such combined fueling stations largely rely on existing infrastructure hence represent a low-cost option for setting up hydrogen fueling facilities. However optimizing the layout of dual petrol-hydrogen fueling stations and their rational site selection is critical for ensuring the efficient use of re sources. This paper investigates the site selection of combined hydrogen and petrol fueling stations at the ter minus of China’s "West-to-East Hydrogen Pipeline" project. A weighting model based on EWM-CRITIC-Game Theory is developed and the weight coefficients derived from game theory are used to perform the compre hensive ranking of potential sites. The combined evaluation results yield an overall ranking of A9 > A4 > A8 > A26 > A20 > A21 > A11. The effectiveness of this novel method is verified by comparing the results with those obtained from Copeland Borda Average and geometric mean methods. Considering the actual distance con straints the final site ranking is A9 > A4 > A8 > A20 > A21 > A11 > A14. This location offers optimal con ditions for infrastructure integration and hydrogen fueling service coverage. The reliability analysis indicates that the proposed game theory-based method delivers strong performance across various scenarios underscoring its reliability and versatility in consistently delivering accurate results.

Hydrogen production from electrolytic water based on Renewable Energy has been found as a vital method for the local consumption of new energy and the utilization of hydrogen energy. In this paper the hydrogen production power supply matching the working characteristics of electrolytic water production was investigated. Through the analysis of the correlation between the electrolysis current and temperature of the proton exchange membrane electrolyzer and the electrolyzer port voltage energy efficiency and hydrogen production speed it was concluded that the hydrogen production power supply should be characterized by low output current ripple high output current and wide range voltage output. To meet the requirements of the system of hydrogen production from electrolytic water based on new energy a hydrogen production power supply scheme was proposed based on Y which is the type three is the phase staggered parallel LLC topology. In the proposed scheme the cavity with three is the phase staggered parallel output is resonated to meet the operating characteristics (high current and low ripple) of the electrolyzer and pulse frequency control is adopted to achieve resonant soft in the switching operation and increase conversion efficiency. Lastly a simulation model and a 6kW experimental prototype were built to verify the rationality and feasibility of the proposed scheme.