China, People’s Republic

The free-piston engine is a type of none-crank engine that could be operated under variable compression ratio and this provides it flexible fuel applicability and low engine emission potential. In this work several 1-D engine models including conventional gasoline engines free-piston gasoline engines and free-piston hydrogen engines have been established. Both engine performance and emission performance under engine speeds between 5–11 Hz and with different equivalent ratios have been simulated and compared. Results indicated that the free-piston engine has remarkable potential for NOx reduction and the largest reduction is 57.37% at 6 Hz compared with a conventional gasoline engine. However the figure of NOx from the hydrogen free-piston engine is slightly higher than that of the gasoline free-piston engine and the difference increases with the increase of engine speed. In addition several factors and their relationships related to hydrogen combustion in the free-piston engine have been investigated and results show that the equivalent ratio ϕ = 0.88 is a vital point that affects NOx production and the ignition advance timing could also affect combustion duration the highest in-cylinder temperature and NOx production to a large extent.

To alleviate the global warming crisis carbon reduction is an inevitable trend of sustainable development. The energy carrier with Hydrogen (H2) is considered to be one of the promising choices for realizing a low-carbon economy. With the increasing penetration level of wind power generation and for well-balancing wind generation fluctuations this paper proposes a low-carbon economic dispatch method for power systems based on mobile hydrogen storage(MHS). The wind power surplus during off-peak load periods is first utilized to generate green H2. Afterward the green H2 is optimally transported to multiple hydrogen storage(HS) stations for generating power electricity by flexibly controlling the electrolysis(EL) methanation(ME) carbon capture(CCS) and H2 power generation processes in such a way the wind power is coordinated with the hydrogen production transport and utilization to reduce the total carbon emission and minimize the operation cost of power systems. Finally the proposed power system low-carbon economic dispatch model is verified by case studies.

Power-to-gas (P2G) facilities use surplus electricity to convert to natural gas in integrated energy systems (IES) increasing the capacity of wind power to be consumed. However the capacity limitation of P2G and the antipeaking characteristic of wind power make the wind abandonment problem still exist. Meanwhile the oxygen generated by P2G electrolysis is not fully utilized. Therefore this study proposes a low-carbon economic dispatch model considering the utilization of hydrogen and oxygen energy. First the two-stage reaction model of P2G is established and the energy utilization paths of hydrogen blending and oxygen-rich deep peaking are proposed. Specifically hydrogen energy is blended into the gas grid to supply gas-fired units and oxygen assists oxygenrich units into deep peaking. Subsequently the stochastic optimization is used to deal with the uncertainty of the system and the objective function and constraints of the IES are given to establish a low-carbon dispatch model under the energy utilization model. Finally the effectiveness of the proposed method is verified based on the modified IEEE 39-node electric network 20-node gas network and 6-node heat network models.

As smart grid develops and renewables advance challenges caused by uncertainties of renewables have been seriously threatening the energy system’s safe operation. Nowadays the integrated electric-gas system (IEGS) plays a significant role in promoting the flexibility of modern grid owing to its great characteristic in accommodating renewable energy and coping with fluctuation and uncertainty of the system. And hydrogen as an emerging and clean energy carrier can further enhance the energy coupling of the IEGS and promote carbon neutralization with the development of power-to-hydrogen (P2H) technology and technology of blending hydrogen in the natural gas system. Dealing with the uncertainty of renewables a robust schedule optimization model for the integrated electric and gas systems with blending hydrogen (IEGSH) considering the dynamics of gas is proposed and the iterative solving method based on column-and-constraint generation (C&CG) algorithm is implemented to solve the problem. Case studies on the IEGSH consisting of IEEE 39-bus power system and 27-node natural gas system validate the effectiveness of the dynamic energy flow model in depicting the transient process of gas transmission. The effectiveness of the proposed robust day-ahead scheduling model in dealing with the intra-day uncertainty of wind power is also verified. Additionally the carbon emission reduction resulting from the blending of hydrogen is evaluated.

Hydrogen energy is considered one of the cleanest and most promising alternatives to fossil fuel because the only combustion product is water. The development of water splitting electrocatalysts with Earth abundance cost-efficiency and high performance for large current density industrial applications is vital for H2 production. However most of the reported catalysts are usually tested within relatively small current densities (< 100 mA cm−2 ) which is far from satisfactory for industrial applications. In this minireview we summarize the latest progress of effective non-noble electrocatalysts for large current density hydrogen evolution reaction (HER) whose performance is comparable to that of noble metal-based catalysts. Then the design strategy of intrinsic activities and architecture design are discussed including self-supporting electrodes to avoid the detachment of active materials the superaerophobicity and superhydrophilicity to release H2 bubble in time and the mechanical properties to resist destructive stress. Finally some views on the further development of high current density HER electrocatalysts are proposed such as scale up of the synthesis process in situ characterization to reveal the micro mechanism and the implementation of catalysts into practical electrolyzers for the commercial application of as-developed catalysts. This review aimed to guide HER catalyst design and make large-scale hydrogen production one step further.

Hydrogen fuel cell vehicle industry is in a rapid development stage. Studying the domestic spatial distribution of hydrogen fuel cell vehicle industry across a country especially the spatio-temporal evolution of the innovation level and position of each region in innovation network will help to understand the industry’s development trends and characteristics and avoid repeated construction. This article uses social network analysis and patent citation information of 2971 hydrogen fuel cell vehicle related invention patents owned by 218 micro-innovators across 25 provinces of China from 2001 to 2020 to construct China’s hydrogen fuel cell vehicle innovation network. Based on the dimensions of knowledge production knowledge consumption and network broker the network positions of sample provinces in three periods divided by four main national policies are classified. The main findings are as follows. 1) In China the total sales of hydrogen fuel cell vehicle and the development of supporting infrastructure are balanced and a series of national and local industrial development polices have been issued. 2) China’s hydrogen fuel cell vehicle innovation network density the proportion of universities and research institutes among the innovators and the active degree of the eastern provinces are all becoming higher. 3) The provinces in optimal network position are all from the eastern region. Shanghai and Liaoning are gradually replaced by Beijing and Jiangsu. 4) Sichuan in the western region is the only network broker based on knowledge consumption. 5) Although Zhejiang Tianjin Hebei Guangdong and Hubei are not yet in the optimal position they are outstanding knowledge producers. Specifically Guangdong is likely to climb to the optimal network position in the next period. The conclusions will help China’s provinces to formulate relevant development policies to optimize industry layout and enhance collaborative innovation in the hydrogen fuel cell vehicle industry.

Alongside the rapid expansion of wind power installation in China wind curtailment is also mounting rapidly due to China’s energy endowment imbalance. The hydrogen-based wind-energy storage system becomes an alternative to solve the puzzle of wind power surplus. This article introduced China’s energy storage industry development and summarized the advantages of hydrogen-based wind-energy storage systems. From the perspective of resource conservation it estimated the environmental benefits of hydrogen-based wind-energy storages. This research also builds a valuation model based on the Real Options Theory to capture the distinctive flexible charging and discharging features of the hydrogen-based wind-energy storage systems. Based on the model simulation results including the investment value and operation decision of the hydrogen energy storage system with different electricity prices system parameters and different levels of subsidies are presented. The results show that the hydrogen storage system fed with the surplus wind power can annually save approximately 2.19–3.29 million tons of standard coal consumption. It will reduce 3.31–4.97 million tons of CO2 SO2 NOx and PM saving as much as 286.6–429.8 million yuan of environmental cost annually on average. The hydrogen-based wind-energy storage system’s value depends on the construction investment and operating costs and is also affected by the meanreverting nature and jumps or spikes in electricity prices. The market-oriented reform of China’s power sector is conducive to improve hydrogen-based wind-energy storage systems’ profitability. At present subsidies are still essential to reduce initial investment and attract enterprises to participate in hydrogen energy storage projects.

Reducing the carbon emissions from trucks is critical to achieving the carbon peak of road freight. Based on the prediction of truck population and well-to-wheel (WTW) emission analysis of traditional diesel trucks and potential clean trucks including natural gas battery-electric plug-in hybrid electric and hydrogen fuel cell the paper analyzed the total greenhouse gas (GHG) emissions of China's road freight under four scenarios including baseline policy facilitation (PF) technology breakthrough (TB) and PF-TB. The truck population from 2021 to 2035 is predicted based on regression analysis by selecting the data from 2002 to 2020 of the main variables such as the GDP scale road freight turnover road freight volume and the number of trucks. The study forecasts the truck population of different segments such as mini-duty trucks (MiDT) light-duty trucks (LDT) medium-duty trucks (MDT) and heavy-duty trucks (HDT). Relevant WTW emissions data are collected and adopted based on the popular truck in China's market PHEVs have better emission intensity especially in the HDT field which reduces by 51% compared with ICEVs. Results show that the scenario of TB and PF-TB can reach the carbon peak with 0.13% and 1.5% total GHG emissions reduction per year. In contrast the baseline and PF scenario fail the carbon peak due to only focusing on the number of clean trucks while lacking the restrictions on the GHG emission factors of energy and ignoring the improvement of trucks' energy efficiency and the total emissions increased by 29.76% and 16.69% respectively compared with 2020. As the insights adopting clean trucks has an important but limited effect which should coordinate with the transition to low carbon energy and the melioration of clean trucks to reach the carbon peak of road freight in China.

With the rapid promotion of renewable energy technologies and the trend to a low-carbon society the positive impacts of an integrated energy system that realizes various forms of energy-utilizing improvement and carbon reduction have fully emerged. Hydrogen with a decarbonized characteristic being integrated into the integrated energy system has become a viable option to offset the intermittency of renewables and decline the fossil fuel usage. An optimal planning model of a wind–photovoltaic–hydrogen storage-integrated energy system with the objective of total economic and environmental cost minimization by considering various energy technology investments is proposed. Case studies are developed to compare the economic and environmental benefits of different energy investment scenarios especially hydrogen applications. The cost–benefit analysis was carried out to prove that hydrogen investment is not a cost-competitive option but can alleviate the burden of carbon emissions somehow. Finally sensitivity analysis of key parameters of sale capacity carbon tax and renewable penetration level was performed to indicate the rational investment for a wind–photovoltaic–hydrogen storage-integrated energy system.

Polymer electrolyte membrane (PEM) fuel cells are electrochemical devices that directly convert the chemical energy stored in fuel into electrical energy with a practical conversion efficiency as high as 65%. In the past years significant progress has been made in PEM fuel cell commercialization. By 2019 there were over 19000 fuel cell electric vehicles (FCEV) and 340 hydrogen refueling stations (HRF) in the U.S. (~8000 and 44 respectively) Japan (~3600 and 112 respectively) South Korea (~5000 and 34 respectively) Europe (~2500 and 140 respectively) and China (~110 and 12 respectively). Japan South Korea and China plan to build approximately 3000 HRF stations by 2030. In 2019 Hyundai Nexo and Toyota Mirai accounted for approximately 63% and 32% of the total sales with a driving range of 380 and 312 miles and a mile per gallon (MPGe) of 65 and 67 respectively. Fundamentals of PEM fuel cells play a crucial role in the technological advancement to improve fuel cell performance/durability and reduce cost. Several key aspects for fuel cell design operational control and material development such as durability electrocatalyst materials water and thermal management dynamic operation and cold start are briefly explained in this work. Machine learning and artificial intelligence (AI) have received increasing attention in material/energy development. This review also discusses their applications and potential in the development of fundamental knowledge and correlations material selection and improvement cell design and optimization system control power management and monitoring of operation health for PEM fuel cells along with main physics in PEM fuel cells for physics-informed machine learning. The objective of this review is three fold: (1) to present the most recent status of PEM fuel cell applications in the portable stationary and transportation sectors; (2) to describe the important fundamentals for the further advancement of fuel cell technology in terms of design and control optimization cost reduction and durability improvement; and (3) to explain machine learning physics-informed deep learning and AI methods and describe their significant potentials in PEM fuel cell research and development (R&D).