China, People’s Republic

Multi-energy systems (MESs) can address issues such as low renewable energy utilization and power imbalances by optimizing the integration of various energy sources. This paper proposes an optimization operation strategy for MES to regulate the hydrogen and battery storage system (HBRS) based on carbon emission factors (CEFs). Insufficient renewable energy utilization caused by reverse peak regulation can be addressed by guiding the optimal output of HBRS through this model thereby achieving multi-energy complementarity. The CEF is used to balance the output of the HBRS to achieve a low-carbon economic operating system. First the fluctuation of renewable energy is decomposed and reconstructed. Subsequently The HBRS system is utilized to smooth out the fluctuations caused by different frequencies of new energy and then the CEF is used to promote the output of the low-carbon subsystem. Finally comparative verification is conducted across validation cases to demonstrate the effectiveness of the proposed model and the optimization strategy.

This research presents a hierarchically synchronized Multi-Energy System (MES) designed for regional communities incorporating a network of small-scale Integrated Energy Microgrids (IEMs) to augment efficiency and collective advantages. The MES framework innovatively integrates energy complementarity pairing algorithms with efficient iterative optimization processes significantly curtailing operational expenditures for constituent microgrids and bolstering both community-wide benefits and individual microgrid autonomy. The MES encompasses electricity hydrogen and heat resources while leveraging controllable assets such as battery storage systems fuel cell combined heat and power units and electric vehicles. A comparative study of six IEMs demonstrates an operational cost reduction of up to 26.72% and a computation time decrease of approximately 97.13% compared to traditional methods like ADMM and IDAM. Moreover the system preserves data privacy by limiting data exchange to aggregated energy information thus minimizing direct communication between IEMs and the MES. This synergy of multi-energy complementarity iterative optimization and privacy-aware coordination underscores the potential of the proposed approach for scalable community-centered energy systems.

Hydrogen is considered a clean and efficient energy carrier crucial for shapingthe net-zero future. Large-scale production transportation storage and use of greenhydrogen are expected to be undertaken in the coming decades. As the smallest element inthe universe however hydrogen can adsorb on diffuse into and interact with many metallicmaterials degrading their mechanical properties. This multifaceted phenomenon isgenerically categorized as hydrogen embrittlement (HE). HE is one of the most complexmaterial problems that arises as an outcome of the intricate interplay across specific spatialand temporal scales between the mechanical driving force and the material resistancefingerprinted by the microstructures and subsequently weakened by the presence of hydrogen. Based on recent developments in thefield as well as our collective understanding this Review is devoted to treating HE as a whole and providing a constructive andsystematic discussion on hydrogen entry diffusion trapping hydrogen−microstructure interaction mechanisms and consequencesof HE in steels nickel alloys and aluminum alloys used for energy transport and storage. HE in emerging material systems such ashigh entropy alloys and additively manufactured materials is also discussed. Priority has been particularly given to these lessunderstood aspects. Combining perspectives of materials chemistry materials science mechanics and artificial intelligence thisReview aspires to present a comprehensive and impartial viewpoint on the existing knowledge and conclude with our forecasts ofvarious paths forward meant to fuel the exploration of future research regarding hydrogen-induced material challenges.

Industrial alkaline water electrolysis systems face challenges in maintaining hydrogenin-oxygen impurity within safe limits under fluctuating operating conditions. This study aims to characterize the dynamic response of hydrogen-in-oxygen concentration in an industrial 10 kW alkaline water electrolysis test platform (2 Nm3/h hydrogen output at 1.6 MPa and 90 ◦C) and to identify how operating parameters influence hydrogen-inoxygen behavior. We systematically varied the cell current system pressure and electrolyte flow rate while monitoring real-time hydrogen-in-oxygen levels. The results show that hydrogen-in-oxygen exhibits significant inertia and delay: during startup hydrogen-inoxygen remained below the 2% safety threshold and stabilized at 0.9% at full load whereas a step decrease to 60% load caused hydrogen-in-oxygen to rise to 1.6%. Furthermore reducing the pressure from 1.4 to 1.0 MPa lowered the hydrogen-in-oxygen concentration by up to 15% and halving the alkaline flow rate suppressed hydrogen-in-oxygen by over 20% compared to constant conditions. These findings provide new quantitative insights into hydrogen-in-oxygen dynamics and offer a basis for optimizing control strategies to keep gas purity within safe limits in industrial-scale alkaline water electrolysis systems.

In response to the surging global demand for clean energy solutions and sustainability hydrogen is increasingly recognized as a key player in the transition towards a low-carbon future necessitating efficient storage and transportation methods. The utilization of natural geological formations for underground storage solutions is gaining prominence ensuring continuous energy supply and enhancing safety measures. However this approach presents challenges in understanding gas-rock interactions. To bridge the gap this study proposes a data-driven strategy for contact angle prediction using machine learning techniques. The research leverages a comprehensive dataset compiled from diverse literature sources comprising 1045 rows and over 5200 data points. Input features such as pressure injection rate temperature salinity rock type and substrate were incorporated. Various artificial intelligence algorithms including Support Vector Machine (SVM) k-Nearest Neighbors (KNN) Feedforward Deep Neural Network (FNN) and Recurrent Deep Neural Network (RNN) were employed to predict contact angle with the FNN algorithm demonstrating superior performance accuracy compared to others. The strengths of the FNN algorithm lie in its ability to model nonlinear relationships scalability to large datasets robustness to noisy inputs generalization to unseen data parallelizable training processes and architectural flexibility. Results show that the FNN algorithm demonstrates higher accuracy (RMSE = 0.9640) than other algorithms (RMSERNN = 1.7452 RMSESVM = 1.8228 RMSEKNN = 1.0582) indicating its efficacy in predicting the contact angle testing subset within the context of underground hydrogen storage. The findings of this research highlight a low-cost and reliable approach with high accuracy for estimating contact angle of water–hydrogen–rock system. This technique also helps determine the contribution and influence of independent factors aiding in the interpretation of absorption tendencies and the ease of hydrogen gas flow through the porous rock space during underground hydrogen storage.

Pipeline steel is highly susceptible to hydrogen embrittlement (HE) in hydrogen environments which compromises its structural integrity and operational safety. Existing studies have primarily focused on the degradation trends of mechanical properties in hydrogen environments but there remains a lack of quantitative failure prediction models. To investigate the failure behavior of X65 pipeline steel under hydrogen environments this paper utilized notched round bar specimens with three different radii and smooth round bar specimens to examine the effects of pre-charging time the coupled influence of stress triaxiality and hydrogen concentration and the coupled influence of strain rate and hydrogen concentration on the HE sensitivity of X65 pipeline steel. Fracture surface morphologies were characterized using scanning electron microscopy (SEM) revealing that hydrogen-enhanced localized plasticity (HELP) dominates failure mechanisms at low hydrogen concentrations while hydrogen-enhanced decohesion (HEDE) becomes dominant at high hydrogen concentrations. The results demonstrate that increasing stress triaxiality or decreasing strain rate significantly intensifies the HE sensitivity of X65 pipeline steel. Based on the experimental findings failure prediction models for X65 pipeline steel were developed under the coupled effects of hydrogen concentration and stress triaxiality as well as hydrogen concentration and strain rate providing theoretical support and mathematical models for the engineering application of X65 pipeline steel in hydrogen environments.

China has emerged as a global leader in promoting new energy vehicles; however the impact of these efforts on the commercial vehicle sector remains limited. Hydrogen fuel cell vehicles are crucial for improving the environmental performance of commercial vehicles in China. This study evaluates the effectiveness of China’s Hydrogen fuel cell vehicle policies. Firstly an evaluation index system for hydrogen fuel cell vehicle policies is established quantifying the policy through two key metrics: policy comprehensiveness and policy synergy. Subsequently city-level data from 84 municipalities (2018-2022) are analyzed to assess policy impacts on hydrogen fuel cell vehicles adoption. The results show that both policy comprehensiveness and synergy significantly drive hydrogen fuel cell vehicle sales growth. Early sales figures also strongly influence current trends. Therefore promoting growth in hydrogen fuel cell vehicle sales can further enhance policy efforts while also accounting for the cumulative effects of initial promotional activities.

Ports are critical hubs in the global supply chain yet they face mounting challenges in achieving carbon neutrality. Port Integrated Multi-Energy Systems (PIMESs) offer a comprehensive solution by integrating renewable energy sources such as wind photovoltaic (PV) hydrogen and energy storage with traditional energy systems. This study examines the implementation of a real-word PIMES showcasing its effectiveness in reducing energy consumption and emissions. The findings indicate that in 2024 the PIMES enabled a reduction of 1885 tons of CO2 emissions with wind energy contributing 84% and PV 16% to the total decreases. The energy storage system achieved a charge–discharge efficiency of 99.15% while the hydrogen production system demonstrated an efficiency of 63.34% producing 503.87 Nm3/h of hydrogen. Despite these successes challenges remain in optimizing renewable energy integration expanding storage capacity and advancing hydrogen technologies. This paper highlights practical strategies to enhance PIMESs’ performances offering valuable insights for policymakers and port authorities aiming to balance energy efficiency and sustainability and providing a blueprint for carbon-neutral port development worldwide.

It is believed that hydrogen will play an essential role in energy transition and achieving the net-zero target by 2050. Currently global hydrogen production mostly relies on processing fossil fuels such as coal and natural gas commonly referred to as grey hydrogen production while releasing substantial amounts of carbon dioxide (CO2). Developing economically and technologically viable pathways for hydrogen production while eliminating CO2 emissions becomes paramount. In this critical review we examine the common grey hydrogen production techniques by analyzing their technical characteristics production efficiency and costs. We further analyze the integration of carbon capture utilization and storage (CCUS) technology establishing the zero-carbon strategy transiting from grey to blue hydrogen production with CO2 capture and either utilized or permanently stored. Today grey hydrogen production exhibits technological diversities with various commercial maturities. Most methods rely on the effectiveness of catalysts necessitating a solution to address catalyst fouling and sintering in practice. Although CCUS captures utilizes or stores CO2 during grey hydrogen production its wide application faces multiple challenges regarding the technological complexity cost and environmental benefits. It is urgent to develop technologically mature low-cost and low-energy-consumption CCUS technology implementing extensive large-scale integrated pilot projects.

In the context of “dual carbon” in order to promote the consumption of renewable energy and improve energy utilization efficiency a low-carbon economic dispatch model of an integrated energy system containing carbon capture power plants and multiple utilization of hydrogen energy is proposed. First introduce liquid storage tanks to transform traditional carbon capture power plants and at the same time build a multi-functional hydrogen utilization structure including two-stage power-to-gas hydrogen fuel cells hydrogen storage tanks and hydrogen-doped cogeneration to fully exploit hydrogen. It can utilize the potential of collaborative operation with carbon capture power plants; on this basis consider the transferability and substitutability characteristics of electric heating gas load and construct an electric heating gas comprehensive demand response model; secondly consider the mutual recognition relationship between carbon quotas and green certificates Propose a green certificate-carbon trading mechanism; finally establish an integrated energy system with the optimization goal of minimizing the sum of energy purchase cost demand response compensation cost wind curtailment cost carbon storage cost carbon purchase cost carbon trading cost and green certificate trading compensation. Optimize scheduling model. The results show that the proposed model can effectively reduce the total system cost and carbon emissions improve clean energy consumption and energy utilization and has significant economical and low-carbon properties.