China, People’s Republic

Transitioning to renewable energy is vital to achieving decarbonization at the global level but energy storage is still a major challenge. This review discusses the role of energy storage in the energy transition and the blue economy focusing on technological development challenges and directions. Effective storage is vital for balancing intermittent renewable energy sources like wind solar and marine energy with the power grid. The development of battery technologies hydrogen storage pumped hydro storage and emerging technologies like sodium-ion and metal-air batteries is discussed for their potential for large-scale deployment. Shortages in critical raw materials environmental impact energy loss and costs are some of the challenges to large-scale deployment. The blue economy promises opportunities for offshore energy storage notably through ocean thermal energy conversion (OTEC) and compressed air energy storage (CAES). Moreover the capacity of datadriven optimization and artificial intelligence to enhance storage efficiency is discussed. Policy interventions and economic incentives are necessary to spur the development and deployment of sustainable energy storage technology. Education and workforce training are also important in cultivating future researchers engineers and policymakers with the ability to drive energy innovation. Merging sustainability training with an interdisciplinary approach can potentially establish an efficient workforce that is capable of addressing energy issues. Future work needs to focus on higher energy density efficiency recyclability and cost-effectiveness of the storage technologies without sacrificing their environmental sustainability. The study underlines the need for converging technological economic and educational approaches to enable a sustainable and resilient energy future.

Hydrogen fuel cell vessels represent a vital direction for green shipping but the risk of large-scale hydrogen leakage and diffusion in their enclosed compartments is particularly prominent. To enhance safety a simplified three-dimensional model of the deck-level cabins of the “Water-Go-Round” passenger ship was established using SolidWorks (2023) software. Based on a hydrogen leakage and diffusion model the effects of leakage location leakage aperture and initial ambient temperature on the diffusion patterns and distribution of hydrogen within the cabins were investigated using FLUENT software. The results show that leak location significantly affects diffusion direction with hydrogen leaking from the compartment ceiling diffusing horizontally much faster than from the floor. When leakage occurs at the compartment ceiling hydrogen can reach a maximum horizontal diffusion distance of up to 5.04 m within 540 s; the larger the leak aperture the faster the diffusion with a 10 mm aperture exhibiting a 40% larger diffusion range than a 6 mm aperture at 720 s. The study provides a theoretical basis for the safety design and risk prevention of hydrogen fuel cell vessels.

Amid escalating global climate crises and the urgent imperative to meet the Paris Agreement’s carbon neutrality targets the steel industry—a leading contributor to global greenhouse gas emissions—confronts unprecedented challenges in driving sustainable industrial transformation through innovative low-carbon steelmaking technologies. This paper examines decarbonization technologies across three stages (source process and end-of-pipe) for two dominant steel production routes: the long process (BF-BOF) and the short process (EAF). For the BF-BOF route carbon reduction at the source stage is achieved through high-proportion pellet charging in the blast furnace and high scrap ratio utilization; at the process stage carbon control is optimized via bottom-blowing O2-CO2-CaO composite injection in the converter; and at the end-of-pipe stage CO2 recycling and carbon capture are employed to achieve deep decarbonization. In contrast the EAF route establishes a low-carbon production system by relying on green and efficient electric arc furnaces and hydrogen-based shaft furnaces. At the source stage energy consumption is reduced through the use of green electricity and advanced equipment; during the process stage precision smelting is realized through intelligent control systems; and at the end-of-pipe stage a closed-loop is achieved by combining cascade waste heat recovery and steel slag resource utilization. Across both process routes hydrogen-based direct reduction and green power-driven EAF technology demonstrate significant emission reduction potential providing key technical support for the low-carbon transformation of the steel industry. Comparative analysis of industrial applications reveals varying emission reduction efficiencies economic viability and implementation challenges across different technical pathways. The study concludes that deep decarbonization of the steel industry requires coordinated policy incentives technological innovation and industrial chain collaboration. Accelerating large-scale adoption of low-carbon metallurgical technologies through these synergistic efforts will drive the global steel sector toward sustainable development goals. This study provides a systematic evaluation of current low-carbon steelmaking technologies and outlines practical implementation strategies contributing to the industry’s decarbonization efforts.

To address the collaborative optimization challenge in multi-microgrid systems with significant renewable energy integration this study presents a dual-layer optimization model incorporating power-hydrogen coupling. Firstly a hydrogen energy system coupling framework including photovoltaics storage batteries and electrolysis hydrogen production/fuel cells was constructed at the architecture level to realize the flexible conversion of multiple energy forms. From a modeling perspective the upper-layer optimization aims to minimize lifecycle costs by determining the optimal sizing of distributed PV systems battery storage hydrogen tanks fuel cells and electrolyzers within the microgrid. At the lower level a distributed optimization framework facilitates energy sharing (both electrical and hydrogen-based) across microgrids. This operational layer maximizes yearly system revenue while considering all energy transactions—both inter-microgrid and grid-to-microgrid exchanges. The resulting operational boundaries feed into the upper-layer capacity optimization with the optimal equipment configuration emerging from the iterative convergence of both layers. Finally the actual microgrid in a certain area is taken as an example to verify the effectiveness of the proposed method.

Hydrogen production from water electrolysis can not only reduce greenhouse gas emissions but also has abundant raw materials which is one of the ideal ways to produce hydrogen from new energy. The hydrogen production power supply is the core component of the new energy electrolytic water hydrogen production device and its characteristics have a significant impact on the efficiency and purity of hydrogen production and the service life of the electrolytic cell. In essence the DC/DC converter provides the large current required for hydrogen production. For the converter its input still needs the support of a DC power supply. Given the maturity and technical characteristics of new energy power generation integrating energy storage into offshore energy systems enables stable power supply. This configuration not only mitigates energy fluctuations from renewable sources but also further reduces electrolysis costs providing a feasible pathway for large-scale commercialization of green hydrogen production. First this paper performs a simulation analysis on the wind–solar hybrid energy storage power generation system to demonstrate that the wind–solar–storage system can provide stable power support. It places particular emphasis on the significance of hydrogen production power supply design—this focus stems primarily from the fact that electrolyzers impose specific requirements on high operating current levels and low current ripple which exert a direct impact on the electrolyzer’s service life hydrogen production efficiency and operational safety. To suppress the current ripple induced by high switching frequency and high output current traditional approaches typically involve increasing the output inductor. However this method substantially increases the volume and weight of the device reduces the rate of current change and ultimately results in a degradation of the system’s dynamic response performance. To this end this paper focuses on developing a virtual impedance control technology aiming to reduce the ripple amplitude while avoiding an increase in the filter inductor. Owing to constraints in current experimental conditions this research temporarily relies on simulation data. Specifically a programmable power supply is employed to simulate the voltage output of the wind–solar–storage hybrid system thereby bringing the simulation as close as possible to the actual operating conditions of the wind–solar–storage hydrogen production system. The experimental results demonstrate that the proposed method can effectively suppress the ripple amplitude maintain high operating efficiency and ultimately meet the expected research objectives. That makes it particularly suitable as a high-quality power supply for offshore hydrogen production systems that have strict requirements on volume and weight.

As the global push for carbon neutrality accelerates energy efficiency has become essential for sustainable development especially for nations like Nigeria that face rising energy demands and significant environmental challenges. This study explores how integrating energy efficiency with carbon neutrality can support Nigeria’s strategic energy goals while offering global lessons for other countries facing similar challenges focusing on key sectors including industry transport and power generation. The study systematically examines the impacts of renewable energy (RE) technologies like solar wind and hydropower—alongside policy reforms technological innovations and demand-side management strategies to advance energy efficiency in Nigeria. Key findings include the identification of strategic policy frameworks technological solutions and the transformative role of green hydrogen in decarbonizing hard-to-electrify sectors. The study also emphasizes the importance of international climate finance decentralized RE systems like solar mini-grids for improving energy access and economic opportunities for job creation in the RE sector. Furthermore it highlights the need for behavioral changes community engagement and consistent policy implementation to address infrastructure gaps and drive energy efficiency goals. The novelty of this research lies in its scenario-based analysis of Nigeria’s low-carbon transition detailing both the opportunities and challenges such as policy inconsistencies infrastructure deficits and financial constraints. The findings stress the importance of international collaboration technological advancements and targeted investments to overcome these challenges. By offering actionable insights and strategic recommendations this study provides a roadmap for policymakers industry stakeholders and researchers to drive Nigeria towards a sustainable carbon-neutral future by 2050.

Ammonia is a highly promising zero-carbon fuel for engines. However it exhibits high ignition energy slow flame propagation and severe pollutant emissions so it is usually burned in combination with highly reactive fuels such as hydrogen. An accurate understanding and modeling of ammonia–hydrogen combustion is of fundamental and practical significance to its application. Deep Neural Networks (DNNs) demonstrate significant potential in autonomously learning the interactions between high-dimensional inputs. This study proposed a deep neural network-based method for optimizing chemical reaction mechanism parameters producing an optimized mechanism file as the final output. The novelty lies in two aspects: first it systematically compares three DNN structures (Multilayer perceptron (MLP) Convolutional Neural Network and Residual Regression Neural Network (ResNet)) with other machine learning models (generalized linear regression (GLR) support vector machine (SVM) random forest (RF)) to identify the most effective structure for mapping combustion-related variables; second it develops a ResNet-based surrogate model for ammonia–hydrogen mechanism optimization. For the test set (20% of the total dataset) the ResNet outperformed all other ML models and empirical correlations achieving a coefficient of determination (R2 ) of 0.9923 and root mean square error (RMSE) of 135. The surrogate model uses the trained ResNet to optimize mechanism parameters based on a Stagni mechanism by mapping the initial conditions to experimental IDT. The results show that the optimized mechanism improves the prediction accuracy on laminar flame speed (LFS) by approximately 36.6% compared to the original mechanism. This method while initially applied to the optimization of an ammonia–hydrogen combustion mechanism can potentially be adapted to optimize mechanisms for other fuels.

Dating back to more than one century ago the photocatalysis process has demonstrated great promise in addressing environmental problems and the energy crisis. Nevertheless some single or binary composite materials cannot meet the requirements of large-scale implementations owing to their limited photocatalytic efficiencies. Since 2021 dual S-scheme heterojunctionbased nanocomposites have been undertaken as highly efficient photoactive materials for green energy production and environmental applications in order to overcome limitations faced in traditional photocatalysts. Herein state-of-the-art protocols designed for the synthesis of dual S-scheme heterojunctions are described. How the combined three semiconductors in dual S-scheme heterojunctions can benefit from one another to achieve high energy production and efficient oxidative removal of various pollutants is deeply explained. Photocatalytic reaction mechanisms by paying special attention to the creation of Fermi levels (Ef ) and charge carriers transfer between the three semiconductors in dual S-scheme heterojunctions are discussed. An entire section has been dedicated to some examples of preparation and applications of double S-scheme heterojunction-based nanocomposites for several photocatalytic applications such as soluble pollutants photodegradation bacteria disinfection artificial photosynthesis H2 generation H2O2 production CO2 reduction and ammonia synthesis. Lastly the current challenges of dual S-scheme heterojunctions are presented and future research directions are presented. To sum up dual S-scheme heterojunction nanocomposites are promising photocatalytic materials in the pursuit of sustainable energy production and environmental remediation. In the future dual S-scheme heterojunctions are highly recommended for photoreactors engineering instead of single or binary photocatalysts to drive forward photocatalysis processes for practical green energy production and environmental protection.

Marine and island power systems usually incorporate various forms of energy supply which poses challenges to the coordinated control of the system under diverse irregular and complex load operation modes. To improve the stability and self-sufficiency of island-isolated microgrids with high penetration of renewable energy this study proposes a coordinated control strategy for an island microgrid with PV HGT and HESS combining primary power allocation via low-pass filtering with a fuzzy logic-based secondary correction. The fuzzy controller dynamically adjusts power distribution based on the states of charge of the battery and supercapacitor following a set of predefined rules. A comprehensive system model is developed in Matlab R2023b integrating PV generation an electrolyzer HGT and a battery–supercapacitor HESS. Simulation results across four operational cases demonstrate that the proposed strategy reduces DC bus voltage fluctuations to a maximum of 4.71% (compared to 5.63% without correction) with stability improvements between 0.96% and 1.55%. The HESS avoids overcharging and over-discharging by initiating priority charging at low SOC levels thereby extending service life. This work provides a scalable control framework for enhancing the resilience of marine and island microgrids with high renewable energy penetration.

The rational design of Cu-based catalysts with tailored interfacial structures and electronic states remains challenging yet essential for advancing hydrogen production via methanol steam reforming (MSR). Here we developed a samarium-mediated strategy to construct a 30Sm-CuAl catalyst. The introduction of Sm promotes Cu dispersion and induces strong metal-support interactions resulting in the formation of Sm2O3- encapsulated Cu nanoparticles enriched with Cu+ -O-Sm interfaces. The optimized 30Sm-CuAl demonstrates exceptional MSR performance achieving a hydrogen production rate of 1126 mmol gcat− 1 h− 1 at 250◦C. Mechanistic studies revealed that the reaction follows the formate pathway in xSm-CuAl with formate accumulation identified as the primary reason for the deactivation of 30Sm-CuAl. Dynamic regeneration of 30SmCuAl through redox treatment restores its activity thereby enabling cyclic operation. These findings provide insights into rare-earth oxide regulation of Cu-based catalysts and lay the foundation for targeted resolution of formate intermediate accumulation to enhance MSR stability.