Applications & Pathways

Reducing CO2 emissions in general aviation is a critical challenge where battery electric and fuel cell technologies face limitations in energy density cost and robustness. As a result hydrogen (H2) dual-fuel combustion is a promising alternative but its practical implementation is constrained by abnormal combustion phenomena such as knocking and pre-ignition which limit the achievable H2 energy share. In response to these challenges this paper focuses on strategies to mitigate these irregular combustion phenomena while effectively increasing the H2 energy share. Experimental evaluations were conducted on an engine test bench using a one-cylinder dual-fuel H2 kerosene (Jet A-1) engine utilizing two strategies including water injection (WI) and rising the air–fuel ratio (AFR) by increasing the boost pressure. Additionally crucial combustion characteristics and emissions are examined and discussed in detail contributing to a comprehensive understanding of the outcomes. The results indicate that these strategies notably increase the maximal possible hydrogen energy share with potential benefits for emissions reduction and efficiency improvement. Finally through the use of 0D/1D simulations this paper offers critical thermodynamic and efficiency loss analyses of the strategies enhancing the understanding of their overall impact.

Introduction: With the increasing demand for energy utilization efficiency and minimization of environmental carbon emissions in industrial parks optimizing the configuration and scheduling of integrated energy systems has become crucial. This study focuses on integrated energy systems with massive flexible load resources aiming to maximize energy utilization efficiency while reducing environmental impact. Methods: To model the uncertainties in wind and solar power outputs we employed three-parameter Weibull distribution models and Beta distribution models. Flexible loads were categorized into three types to match different electricity consumption patterns. Additionally an enhanced Kepler Optimization Algorithm (EKOA) was proposed incorporating chaos mapping and adaptive learning rate strategies to improve search scope convergence speed and solution efficiency. The effectiveness of the proposed optimization scheduling and configuration methods was validated through a case study of an industrial park located in a coastal area of southeastern China. Results: The results show that using three-parameter Weibull distribution models and Beta distribution models more accurately reflects the variations in actual wind speeds and solar irradiance levels achieving peak shaving and valley filling effects and enhancing renewable energy utilization. The EKOA algorithm significantly reduced curtailment rates of wind and solar power generation while achieving substantial economic benefits. Compared with other operation modes of hydrogen the daily average cost is reduced by 12.92% and external electricity purchases are reduced by an average of 20.2 MW h/day. Discussion: Although our approach shows potential in improving energy utilization efficiency and economic gains this paper only considered hydrogen energy for single-use pathways and did not account for the economic benefits from selling hydrogen in the market. Future research will further incorporate hydrogen demand response mechanisms and optimize the output of integrated energy systems from the perspective of spot markets. These findings provide valuable references for relevant engineering applications.

This study focuses on the power systems of inland waterway vessels in Chinese Yangtze River systematically outlining the low-carbon technology pathways for different power system types. A comparative analysis is conducted on the technical feasibility emission reduction potential and economic viability of LNG methanol ammonia pure electric and hybrid power systems revealing the bottlenecks hindering the large-scale application of each system. Key findings indicate that: (1) LNG and methanol fuels offer significant short-term emission reductions in internal combustion engine power systems yet face constraints from methane slip and insufficient green methanol production capacity respectively; (2) ammonia enables zero-carbon operations but requires breakthroughs in combustion stability and synergistic control of NOX; (3) electric vessels show high decarbonization potential but battery energy density limits their range while PEMFC lifespan constraints and SOFC thermal management deficiencies impede commercialization; (4) hybrid/range-extended power systems with superior energy efficiency and lower retrofitting costs serve as transitional solutions for existing vessels though challenged by inadequate energy management strategies and multi-equipment communication protocol interoperability. A phased transition pathway is proposed: LNG/methanol engines and hybrid systems dominate during 2025–2030; ammonia-powered systems and solid-state batteries scale during 2030–2035; post-2035 operations achieve zero-carbon shipping via green hydrogen/ammonia.

To reduce fossil fuel dependency in shipping adopting alternative fuels and innovative propulsion systems is essential. Solid Oxide Fuel Cells (SOFC) powered by hydrogen carriers represent a promising solution. This study investigates a multi-fuel SOFC system for ocean-going vessels capable of operating with ammonia methanol or hydrogen thus enhancing bunkering flexibility. A thermodynamic model is developed to simulate the performance of a 3 kW small-scale system subsequently scaling up to a 10 MW configuration to meet the power demand of a container ship used as the case study. Results show that methanol is the most efficient fueling option reaching a system efficiency of 58% while ammonia and hydrogen reach slightly lower values of about 55% and 51% respectively due to higher auxiliary power consumption. To assess technical feasibility two installation scenarios are considered for accommodating multiple fuel tanks. The first scenario seeks the optimal fuel share equivalent to the diesel tank’s chemical energy (17.6 GWh) minimizing mass increase. The second scenario optimizes the fuel share within the available tank volume (1646 m3 ) again minimizing mass penalties. In both cases feasibility results have highlighted that changes are needed in terms of cargo reduction equal to 20.3% or alternatively in terms of lower autonomy with an increase in refueling stops. These issues can be mitigated by the benefits of increased bunkering flexibility

This report assesses the market readiness of zero-emission heavy-duty vehicles and the required infrastructure to meet the 45% emission reduction targets set by the revised CO2 standards by 2030. Achieving these goals requires the widespread adoption of zero-emission vehicles and a robust recharging and hydrogen refuelling infrastructure Three main aspects are investigated: the market readiness of the vehicles considering both the demand and supply side the corresponding infrastructure requirements and the barriers. Building on the inputs of the stakeholders a ‘study scenario’ is developed. This scenario shows a concrete picture of what the zero-emission heavy-duty vehicle fleet and its infrastructure requirement could look like by 2030. There are however key barriers that need to be overcome such as high total cost of ownership limited electricity grid capacity lengthy permitting processes and uncertainty in hydrogen availability and pricing. Stakeholders also emphasize the importance of policy drivers such as emissions trading systems and tolling and tax reforms to stimulate demand. In conclusion achieving the 2030 targets demands a coordinated approach involving manufacturers operators and policymakers to address infrastructure gaps market barriers and policy incentives ensuring the transition to a zero-emission HDV fleet.

The use of hydrogen as a fuel for piston engines enables environmentally friendly and efficient operation. However several challenges arise in the combustion process limiting the development of hydrogen engines. These challenges include abnormal combustion the high burning velocity of hydrogen-enriched mixtures increased nitrogen oxide emissions and others. A rational organization of hydrogen combustion can partially or fully mitigate these issues through the use of advanced methods such as late direct injection charge stratification dual injection jet-guided operation and others. However mathematical models describing hydrogen combustion for these methods are still under development complicating the optimization and refinement of hydrogen engines. Previously we proposed a mathematical model based on Wiebe functions to describe premixed and diffusion combustion as well as relatively slow combustion in lean-mixture zones behind the flame front and near-wall regions. This study further develops the model by accounting for the combined influence of the mixture composition and engine speed mixture stratification and the effects of injection and ignition parameters on premixed and diffusion combustion. Special attention is given to combustion modeling in an engine with single injection and jet-guided operation.

With the global commercialization of hydrogen fuel cell vehicles the number of hydrogen refueling stations is steadily increasing. On-site hydrogen production stations are expected to play a key role in future power systems by absorbing renewable energy and supplying electricity during peak grid loads aiding in peak shaving and load leveling. However renewable energy sources like photovoltaic (PV) systems have highly fluctuating power generation curves making it difficult to provide stable energy for hydrogen production. Traditional stations mainly use alkaline electrolyzers (AE) which are sensitive to power fluctuations leading to operational instability. To address this this paper proposes using capacitors and energy storage batteries to mitigate PV fluctuations and introduces a combined AE and Proton Exchange Membrane (PEM) electrolyzer hydrogen production method. Study cases demonstrate that capacitors and energy storage batteries reduce the variance of PV power output by approximately 0.02. Building on this the hybrid approach leverages the low cost of AE and the rapid response of PEM electrolyzers to better adapt to PV fluctuations and maximize PV absorption. The model is mathematically formulated and the station’s equipment planning and operational strategy are optimized using CPLEX. The results show that compared to pure AE and PEM hydrogen production the combined AE and PEM hydrogen production method reduces the total annual cost of the hydrogen refueling station by 4.3% and 5.9% respectively.

Decarbonizing the steel industry will require a shift towards renewable energy. However costs and emissions associated with the long-distance transport of renewable energy carriers may incentivize the relocation of steel production closer to renewable energy sources. This “green relocation” would affect regional economic structures and global trade patterns. Nevertheless the macroeconomic and environmental impacts of alternative industry location options remain underexplored. This study compares the impacts on value-added prices and emissions under two options for decarbonizing the Dutch steel industry: importing green hydrogen from Brazil to produce green steel in the Netherlands versus relocating production to Brazil and transporting green steel to the Netherlands. Impacts are analyzed by combining a price and a quantity model within an environmentally extended multiregional input-output (EE-MRIO) framework. Results suggest that the relocation option brings the greatest synergies between climate and economic goals at the global level as it leads to lower production costs smaller price effects and greater emissions reductions. However relocation also results in stronger distributive impacts across global regions. Higher carbon prices would be insufficient to counteract relocation incentives. This calls for policymakers in industrialized countries to systematically consider the possibility of green relocation when designing decarbonization and industrial competitiveness strategies.

Model predictive control (MPC) requires high accuracy of the model. However the actual power system has complex dynamic characteristics. There must be unmodeled dynamics in the system modeling process which makes it difficult for MPC to perform the function of optimal control. ESO has the ability to observe and suppress errors combining the both can solve this problem. Thus this paper proposes a coordinated control strategy of hydrogen-energy storage system based on disturbance-rejection model predictive controller. Firstly this paper constructs the state-space model of the system and improves MPC. By connecting ESO and MPC in series this paper designs a matched disturbance-rejection model predictive controller and analyzes the robustness of the research system. Finally this paper verifies the effectiveness and feasibility of the disturbance-rejection model predictive controller under various working conditions. Compared with the method using only MPC the dynamic response time of the system frequency regulation under the proposed strategy in this paper is increased by about 29.9 % and the frequency drop rate is slowed down by 13.5 %. In addition under the AGC command and continuous load disturbance working conditions the maximum frequency deviation of the system under the proposed strategy is reduced by about 54.01 % and 48.96 %. The results clearly show that the proposed strategy in this paper significantly improves the dynamic response ability of the system and reduces the frequency fluctuation of the system after disturbance.

The spark-ignited (SI) hydrogen combustion engine has the potential to noticeably reduce greenhouse gas emissions from passenger cars. To prevent nitrogen oxide emissions and to increase fuel efficiency and power output complex air paths and operating strategies are utilized. This makes the engine control problem more complex challenging the conventional engine calibration process. This work combines and extends the state-of-the-art in real-time combustion engine modeling and optimal control presenting a novel control concept for the efficient operation of a hydrogen combustion engine. The extensive experimental validation with a 1.5 l three-cylinder hydrogen SI engine and a dynamically operated engine test bench with emission and in-cylinder pressure measurements provides a comprehensible comparison to conventional engine control. The results demonstrate that the proposed optimal control decreased the load tracking errors by a factor of up to 2.8 and increased the engine efficiency during lean operation by up to 10 percent while decreasing the calibration effort compared to conventional engine control.