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Abstract To actively promote the strategy of carbon neutrality, the high-carbon emission industry, represented by thermal power plants, is in urgent need of green and low-carbon transformation and development. Carbon capture technology serves as a crucial support for ensuring energy security while achieving carbon neutrality in China. However, after years of development, this technology still faces challenges such as high energy consumption and difficulties in long-term operation, along with a lack of large-scale demonstrations. In response, CHN ENERGY has proactively engaged in technological advancements and established Asia's largest carbon capture demonstration project at the Taizhou Power Plant, with a capacity of 500,000 tonnes per year. Since its official operation in June 2023, the project has been running stably for over 400 consecutive days, with a capture thermal consumption of 2.35 GJ/tCO2 and an electrical consumption of 51.5 kWh/tCO2. It has broken through the bottlenecks of long-term operation in large-scale carbon capture projects, leading the traditional energy industry toward a green and low-carbon transformation.

Abstract Selecting a sustainable heat energy supply system for high-altitude, cold-climatic communities in developing countries is essential for both decision-makers and the scientific community. However, no comprehensive guide or framework exists to address this issue and decarbonize cold communities sustainably. This research aims to fill that gap by identifying and developing a methodology for selecting a suitable heat energy supply system, using Kyrgyzstan as a case study. The approach takes into account renewable energy sources, local conditions, and specific criteria necessary for designing a sustainable energy supply. The paper introduces a decision-making framework based on 17 criteria, covering geographical, environmental, economic, technical, and social aspects, derived from the opinions of over 20 experts. This framework serves as a guide for selecting and designing an appropriate heat energy supply system. Five heat supply options are analyzed in Kyrgyzstan’s high-altitude, cold rural setting to demonstrate the framework's potential. The analysis reveals that centralized district heating is the most suitable solution, scoring 79% for system selection. This methodology is partially or fully transferable to regions or countries with similar climates and local circumstances, offering a valuable resource for the development of sustainable heat energy solutions in cold, high-altitude communities.

Abstract Against the background of the booming expansion of the global digital economy and increasing emphasis on reducing CO2 emissions, this study from the perspective of the transformation of the digital economy applies the generalized Divisia index method to measure the contribution of the driving factors to CO2 emissions in China. From 2007 to 2022, the country’s CO2 emissions increased cumulatively, with a change rate of 80.85%. Energy consumption and CO2 emissions factor became the main drivers contributing to CO2 emissions, with contribution rates of 40.23% and 50.43%, respectively. Meanwhile, the digital economy’s carbon intensity made a negative contribution to CO2 emissions, with a contribution rate of -9.01%, which shows that the expansion of the digital economy is advantageous for lowering CO2 emissions, and this is also verified in the later analysis. In addition, the amount of CO2 emissions changes varies during different periods such as the 12th and 13th Five-Year Plans, which is inseparable from realistic factors such as the stage of the digital economy development and the strength of policy support. This study puts forward appropriate policy recommendations, such as vigorously enhancing digital industrialization, continuously enhancing the degree of industrial digitization, and enhancing investment in the field of digital economy.

Abstract This study aims to compare the catalytic performance of ZSM-5 and SAPO-34 zeolite catalysts in the conversion of ethanol. Through experiments conducted at different temperatures (773 K and 673 K), it was found that SAPO-34 initially exhibits superior propylene selectivity compared to ZSM-5. However, the propylene yield on SAPO-34 gradually decreases, while the ethylene yield increases with time on stream. density functional theory calculations were employed for the investigation of reaction mechanism. The results indicate that the SAPO-34 catalyst surface favors propylene desorption, which beneficial for its initial high propylene selectivity. Nevertheless, the smaller pore structure of SAPO-34 limits the effective diffusion of products, leading to product accumulation within the pores and potentially causing catalyst coking and deactivation. By combining the experimental results with theoretical calculation, this study not only explored the selectivity difference between SAPO-34 and H-ZSM-5 in ethanol conversion reaction, but also revealed the influence of different molecular sieve catalyst structures on product distribution and catalyst stability.

Abstract A unique and distinctive absorption-thermoelectric cooling system powered by a photovoltaic-thermal unit is presented in this work with a thorough exergy analysis. The photovoltaic module supplied electricity to the thermoelectric cooler, while heat energy fueled the absorption unit. The solar module's efficient cooling enhances electrical output while diminishing the quality of thermal energy. Consequently, the thermoelectric cooler exhibits superior cooling performance compared to the absorption cooler. The primary objectives of the study are the coefficient of performance, exergy efficiency, and cooling capacity of the photovoltaic-thermal absorption system. A mathematical representation of the suggested system is shown. The model is assessed at a local solar irradiance of 1000 W/m² and various operational temperatures. The system coefficient of performance climbed from 0.67 to 0.73, while the exergy efficiency declined from 0.34 to 0.17 as the photovoltaic-thermal temperature rose from 60 to 120 °C, achieving a peak cooling capacity of 6 kW.

Abstract Hydrogen energy is pivotal in the energy transition due to its high efficiency and zero-emission characteristics. However, the potential for explosions constrains its broader application. Gaining insights into the dynamics of overpressure in hydrogen explosions is vital for the safe design of explosion-proof facilities and the determination of equipment spacing. This study investigates hydrogen explosions in open spaces of 1 m³ and 27 m³ volumes, analyzing flame propagation and overpressure distribution. It also evaluates the accuracy of three theoretical models in predicting peak overpressure. The results reveal that the spherical flame from a hydrogen cloud explosion transforms into an ellipsoidal shape upon contact with the ground. The average flame propagation velocity across different equivalent ratio is ordered as follows: Va (φ = 1.0) > Va (φ = 1.5) > Va (φ = 2.5) > Va (φ = 0.5). At equivalent distances, the peak overpressure of hydrogen cloud explosions is comparable across both scales. The traditional trinitrotoluene model overestimates the peak overpressure of hydrogen cloud explosions at both scales. The optimized trinitrotoluene model achieves over 90% accuracy in predicting hydrogen cloud explosions in 1m³ volumes but shows decreased accuracy in 27 m³ explosions. At source intensity level 3, the Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek multi-energy model exhibits a prediction accuracy of over 70% for peak overpressure in hydrogen cloud explosions, with consistent performance across different scales, rendering it a more reliable model for such predictions. This research enhances hydrogen safety assessment technologies by providing a more precise method for evaluating large-scale hydrogen cloud explosion risks.

Abstract For the submerged high-pressure liquid hydrogen pump, a core piece of equipment of liquid hydrogen transportation, extensive analysis, and research were conducted on its components and structure during the development process. By referencing typical failure probabilities in the energy industry and statistical data from prototype pump development and testing, a list of failure probabilities for each part of the liquid hydrogen pump was compiled, and the consequences of those failures were deduced. The nitrogen liquid test experiment verified the possibility of pump seal failure and identified the fault modes. It confirmed that the piston rod seal is one of the critical components prone to failure in the liquid hydrogen pump. Subsequently, six important technical optimization measures for the piston rod seal pair have been carried out, reducing the probability of failure. Moreover, based on the concept of inherent safety, the sealing structure of the piston rod was innovatively designed, transforming hidden failures into visible ones, facilitating timely detection and monitoring of failures, and greatly reducing the safety risks caused by piston rod seal failure. The improved liquid hydrogen pump successfully passed subsequent tests, ensuring its long-term safe operation.

Abstract Addressing climate change and navigating the energy transition are more urgent than ever. Several researchers agree that renewable energy adoption and industrial decarbonization are essential pathways forward. As sectors like transportation and heating become increasingly electrified, energy demand is expected to rise, necessitating innovative solutions. Green and blue hydrogen, touted as potential game changers, hold promise in this transition but require advanced electrolysis technologies, sustainable materials, high-pressure storage systems, and optimized system designs for energy efficiency, safety, and scalability to enable large-scale implementation. This study discusses the critical aspects of offshore green hydrogen production, focusing on key findings related to production methods, electrolyzer technologies, and their associated challenges. Key findings highlight that the levelized cost of hydrogen is significantly influenced by the cost of electricity from offshore wind farms, capital expenditure on electrolyzers, and the logistics of offshore platforms, pipelines, and storage. Hydrogen storage advancements, including metal hydrides and chemical carriers, are vital for realizing green hydrogen’s potential as an energy vector. Additionally, the industrial-scale production of green hydrogen through electrolysis powered by offshore wind offers promising pathways for decarbonizing energy systems. The study also emphasizes the critical role of collaboration between local and international policy stakeholders, industrial partnerships, and institutional support in shaping a favorable future for hydrogen in the global energy transition.

Abstract This review explores the advancements in solar technologies, encompassing production methods, storage systems, and their integration with renewable energy solutions. It examines the primary hydrogen production approaches, including thermochemical, photochemical, and biological methods. Thermochemical methods, though highly efficient, require advanced materials and complex reactor designs, while photochemical methods offer a simpler alternative but suffer from low conversion efficiencies. Biological hydrogen production presents a low-cost option but faces limitations in scalability and production rates. The review also highlights innovative hydrogen storage technologies, such as metal hydrides, metal-organic frameworks, and liquid organic hydrogen carriers, which address the intermittency of solar energy and offer scalable storage solutions. Additionally, the potential of hybrid energy systems that integrate solar hydrogen with photovoltaics, thermal energy systems, battery storage, and smart grids is emphasized. Despite technical and economic barriers, ongoing advancements in catalyst development, material optimization, and artificial intelligence-driven energy management systems are accelerating the adoption of solar hydrogen technologies. These innovations position solar hydrogen as a pivotal solution for achieving a sustainable and low-carbon energy future.

This special issue highlights the generation, application, and safe use of low-carbon hydrogen produced from renewable energy sources.

Abstract Solar photovoltaic energy generation due to its high potential is being adopted as one of the main power sources by many countries to mitigate their climate and electrical power issues. Hence the accurate forecasting becomes important to make grid operations smoother, and for this purpose modern day artificial intelligence technologies can make a significant contribution. This study is an endeavor to target accurate forecasting for different weather conditions by using a simple recurrent neural network, long short-term memory and gated recurrent unit based hybrid model, and bi-directional gated recurrent unit. The experimental dataset has been acquired from Quaid-e-Azam Solar Park, Bahawalpur Pakistan. This study observed that the bi-directional gated recurrent unit outperforms the hybrid model, whereas the simple recurrent neural network lags most in accuracy. The results confirm that the bi-directional gated recurrent unit technique can perform accurately in all critical weather types. Whereas the values of root mean square error, mean absolute error and R square values also ensure the precision of the model for all weather conditions and the best of these parameters for bi-directional gated recurrent unit observed are 0.0012, 0.212, and 0.99 respectively for the overcast dataset.

Abstract Reactivity controlled compression ignition engines use a minimum of two fuels with dissimilar reactivities. The current experimental study examined the effects of compression ratio, hydrogen flow rate, and load on performance, knocking tendency, emissions, and different phases of co-combustion in a hydrogen-diesel reactivity controlled compression ignition engine employing conventional diesel in-cylinder injection and hydrogen induction into the manifold, which reduces the system cost. A constant-speed stationary engine was selected for this study because it has rarely been studied. Compared to the existing literature, wider ranges of hydrogen flow rates (up to 30 slpm) and compression ratios (15–20) were investigated in this study. The results indicate that the maximum brake thermal efficiency was obtained at low hydrogen flow rates (3–5 slpm). Under part-load conditions, the maximum heat release rate and cylinder pressure decreased with an increase in the hydrogen flow rate. At high loads and high compression ratios, a second peak was observed in the heat release curve, the magnitude of which increased with the hydrogen flow rate owing to H2+air premixed combustion. The knocking tendency increased with an increase in the hydrogen flow rate and decrease in the compression ratio. These findings can potentially help in identifying the best operating conditions for stationary constant-speed compression ignition engines adapted for H2-diesel reactivity controlled compression ignition operations, as these engines find wide application in rural economies for powering electric generators, water pumps, and agricultural equipment.

Abstract In designing a modern home with focus on comfort of resident and energy usage optimization simultaneously, the rise of the Internet of Things and incorporation with sensors technology plays a vital role these days. The first and foremost task is to predict the energy consumption in based on available data. This study investigates the integration of artificial neural networks in smart home technology to improve energy usage prediction and efficiency, with compromising the comfort of occupant. A dynamic model based on an artificial neural network model is designed in this study which artificially controls light, heating process and cooling to cut down energy wastage. Data from 114 single-family apartments for energy consumption is collected from year 2014 to 2016. Energy consumption is predicted by current model with an accuracy of up to 99.9% for energy usage patterns. Which helps to optimizing resource management in real time. A robust modeling approach i.e. multi-layer perceptron networks was implemented along with energy usage data. 70% of data is used for training the neural networks and rest for testing and validation purpose. The current defined model shows a significant improvement in prediction accuracy of energy usage and efficiency when compared to state-of-the-art models. Metrics such as R-values and mean square error are employed to check accuracy. These results show the essential role of artificial intelligence in improving energy management for smart buildings, with potential benefits including significant energy usage and loss management to help improve sustainable living.

Abstract This article discusses the solar assisted technologies from the Indian subcontinent to address the sustainable development targets developed by united nations programme. For water and renewable energy, technologies presented in this paper include carbon sequestration, solar biomass, power plants with thermal and photovoltaic systems, irrigation systems, heating systems, dryers, distillation systems, solar desalination, and water treatment. Various techniques are suggested for clean water recovery using solar distillation, solar stills, and desalination. Various methods of solar drying the fruits and vegetables have been discussed using flat plate collector. Power production from solar-thermal, solar-photovoltaic and solar biomass systems are covered from recent studies. Prospects on future solar energy research is recommended on solar cells, magnetized solar stills, heat pump integrated solar power production systems, plasmonic nanofluids in solar collectors. At the conclusion, the outlook for solar technologies is examined.

Abstract The world's increasing human population and industrial activities have resulted in an enormous rise in energy consumption throughout the years. A severe attention has developed regarding an impending energy crisis caused by the depletion of fossil fuel supplies and their contribution to environmental degradation. As a result, it is necessary to investigate and make use of non-fossil energy sources for the purpose of maintaining demand stability as well as creating a sustainable green environment. Pyrolysis is a reliable method to convert materials from municipal solid waste to useful energy. Hence, the co-pyrolysis of unsegregated municipal solid waste was investigated in this study using an integrated two-step pyrolysis by double reactor that was supported by various natural catalysts such as zeolite, dolomite, and kaolin at 550 °C for 210 minutes as constant variables in which it has not been reported previously. To obtain the physical and chemical properties, liquid fuel was subjected to ASTM and gas chromatography-mass spectroscopy analyses and examining the impact of each catalyst on its characteristics. The aromatic fraction was prominent in the liquid fuel yields produced by kaolin and zeolite catalysts (57.4 and 46.1% peak area, respectively). Meanwhile, the greatest liquid fuel was produced by using dolomite as catalyst. The viscosity and density of liquid fuel with dolomite, kaolin, and zeolite were 10.83, 4.25, and 4.04 mm2/s and 0.88, 0.89, and 1.01 g/cm3, respectively. Conversely, the corresponding calorific values for zeolite, kaolin, and dolomite are 41.37, 41.09, and 41.19 MJ/kg. Its physical characteristics are comparable to those of common fuels like petrol-88, which was utilized in Indonesia as a vehicle fuel.