Applications & Pathways

In recent years traditional fossil fuels such as coal oil and natural gas have historically dominated various applications but there has been a growing shift towards cleaner alternatives. Among these alternatives hydrogen (H2) stands out as a highly promising substitute for all other conventional fuels. Today hydrogen (H2) is actively taking on a significant role in displacing traditional fuel sources. The utilization of hydrogen in gas turbine (GT) power generation offers a significant advantage in terms of lower greenhouse gas emissions. The performance of hydrogen-based gas turbines is influenced by a range of variables including ambient conditions (temperature and pressure) component efficiency operational parameters and other factors. Additionally incorporating an intercooler into the gas turbine system yields several advantages such as reducing compression work and maintaining power and efficiency. Many scholars and researchers have conducted comprehensive investigations into the components mentioned above within context of gas turbines (GTs). This study provides an extensive examination of the research conducted on hydrogen-powered gas turbine and intercooler with employed different methods and techniques with a specific emphasis on the different case studies of a hydrogen gas turbine and intercooler. Moreover this study not only examined the current state of research on hydrogen-powered gas turbine and intercooler but also covered its influence by offering the effective recommendations and insightful for guiding for future research in this field.

Reducing the cost of hydrogen fuel cell technology is crucial in propelling the hydrogen economy and achieving decarbonized energy systems. This study identifies the hydrogen fuel cell cost trajectory through a multi-stage learning curve model highlighting technology learning mechanisms across different stages. Findings show that innovation and production contribute to cost reduction and the learning by researching holds a more significant role presently while the learning by doing takes precedence in the long term achieving a 14% learning rate. The cost predictions imply that the system cost of hydrogen fuel cell is expected to fall below 1000 yuan/kW after 2031. Moreover the scenario analyses highlight the conducive role of various hydrogen production technologies and the evolution of cost influencing factors on cost reduction. Our research provides critical insights into the evolving dynamics of technological learning and cost trajectory in the hydrogen fuel cell industry with significant implications for policy-making.

The war in Ukraine caused Europe to more than double its imports of liquefied natural gas (LNG) in only one year. In addition imported LNG remains a crucial source of energy for resource-poor countries such as Japan where LNG imports satisfy about a quarter of the country’s primary energy demand. However an increasing number of countries are formulating stringent decarbonization plans. Liquefied hydrogen and liquefied ammonia coupled with carbon capture and storage (LH2-CCS LNH3-CCS) are emerging as the front runners in the search for low-carbon alternatives to LNG. Yet little is currently known about the full environmental profile of LH2-CCS and LNH3-CCS because several characteristics of the two alternatives have only been analyzed in isolation in previous work. Here we show that the potential of these fuels to reduce greenhouse gas (GHG) emissions throughout the supply chain is highly uncertain. Our best estimate is that LH2-CCS and LNH3-CCS can reduce GHG emissions by 25%–61% relative to LNG assuming a 100 year global warming potential. However directly coupling LNG with CCS would lead to substantial GHG reductions on the order of 74%. Further under certain conditions emissions from LH2-CCS and LNH3-CCS could exceed those of LNG by up to 44%. These results question the suitability of LH2-CCS and LNH3-CCS for stringent decarbonization purposes.

Hydrogen production and storage in hybrid systems is a promising solution for sustainable energy transition decoupling the energy generation from its end use and boosting the deployment of renewable energy. Nonetheless the optimal and cost-effective design of hybrid hydrogen-based systems is crucial to tackle existing limitations in diffusion of these systems. The present study explores net-zero energy management via a multi-objective optimization algorithm for an outdoor test facility equipped with a hydrogen-based hybrid energy production system. Aimed at enabling efficient integration of hydrogen fuel cell system the proposed solution attempts to maximize the renewable factor (RF) and carbon mitigation in the hybrid system as well as to minimize the grid dependency and the life cycle cost (LCC) of the system. In this context the techno-enviroeconomic optimization of the hybrid system is conducted by employing a statistical approach to identify optimal design variables and conflictive objective functions. To examine interactions in components of the hybrid system a series of dynamic simulations are carried out by developing a TRNSYS code coupled with the OpenStudio/EnergyPlus plugin. The obtained results indicate a striking disparity in the monthly RF values as well as the hydrogen production rate and therefore in the level of grid dependency. It is shown that the difference in LCC between optimization scenarios suggested by design of experiments could reach $15780 corresponding to 57% of the mean initial cost. The LCOE value yielded for optimum scenarios varies between 0.389 and 0.537 $/kWh. The scenario with net-zero target demonstrates the lowest LCOE value and the highest carbon mitigation i.e. 828 kg CO2/yr with respect to the grid supply case. However the LCC in this scenario exceeds $57370 which is the highest among all optimum scenarios. Furthermore it was revealed that the lowest RF in optimal scenarios is equal to 66.2% and belongs to the most economical solution.

Hydrogen is considered as an attractive alternative to fossil fuels in the transportation sector. However the penetration of Fuel Cell Electric Vehicles (FCEV) is hindered by the lack of hydrogen refueling station infrastructures. In this study the feasibility of a hybrid PV/wind system for hydrogen refueling station is investigated. Refueling events data is collected in different locations including industrial residential highway and tourist areas. Station Occupancy Fractions (SOF) and Social-to-Solar Fraction (STSF) indicators are developed to assess the level of synchronization between the hydrogen demand and solar potential. Then a validated computer code is used to optimize the renewable system components for off/on-grid cases based on minimizing the Net Present Cost (NPC) and the Loss of Hydrogen Supply Probability (LHSP). For off grid cases the results show that STSF attains maximum value in the industrial area where 0.62 fraction of refueling events occur during the sunshine hours and minimum NPC is achieved. It is observed that when STSF attains lower values of 0.52 0.41 and 0.38 for residential highway and tourist areas NPC increases by 8 16 and 31% respectively. This is associated with lower level of coordination between the hydrogen demand and solar potential. The same conclusion can be stated for the on-grid cases. Therefore for green hydrogen production via solar energy utilization it is recommended that a tariff should be applied to encourage refueling hydrogen vehicles during the availability of solar radiation while reducing the environmental impact storage requirements and eventually the cost of hydrogen production.

This paper proposes a systematic optimization framework to jointly determine the optimal location and sizing decisions of renewables and hydrogen storage in a power network to achieve the transition to low-carbon networks efficiently. We obtain these strategic decisions based on the multi-period alternating current optimal power flow (AC MOPF) problem that jointly analyzes power network renewable and hydrogen storage interactions at the operational level by considering the uncertainty of renewable output seasonality of electricity demand and electricity prices. We develop a tailored solution approach based on second-order cone programming within a Benders decomposition framework to provide globally optimal solutions. In a test case we show that the joint integration of renewable sources and hydrogen storage and consideration of the AC MOPF model significantly reduces the operational cost of the power network. In turn our findings can provide quantitative insights to decision-makers on how to integrate renewable sources and hydrogen storage under different settings of the hydrogen selling price renewable curtailment cost emission tax price and conversion efficiency.

In the quest for a sustainable future energy-intensive industries (EIIs) stand at the forefront of Europe’s decarbonisation mission. Despite their significant emissions footprint the path to comprehensive decarbonisation remains elusive at EU and national levels. This study scrutinises key sectors such as non-ferrous metals steel cement lime chemicals fertilisers ceramics and glass. It maps out their current environmental impact and potential for mitigation through innovative strategies. The analysis spans across Spain Greece Germany and the Netherlands highlighting sector-specific ecosystems and the technological breakthroughs shaping them. It addresses the urgency for the industry-wide adoption of electrification the utilisation of green hydrogen biomass bio-based or synthetic fuels and the deployment of carbon capture utilisation and storage to ensure a smooth transition. Investment decisions in EIIs will depend on predictable economic and regulatory landscapes. This analysis discusses the risks associated with continued investment in high-emission technologies which may lead to premature decommissioning and significant economic repercussions. It presents a dichotomy: invest in climate-neutral technologies now or face the closure and offshoring of operations later with consequences for employment. This open discussion concludes that while the technology for near-complete climate neutrality in EIIs exists and is rapidly advancing the higher costs compared to conventional methods pose a significant barrier. Without the ability to pass these costs to consumers the adoption of such technologies is stifled. Therefore it calls for decisive political commitment to support the industry’s transition ensuring a greener more resilient future for Europe’s industrial backbone.

Fuel cell hybrid electric vehicles have the advantages of zero emission high efficiency and fast refuelling etc. and are one of the key directions for vehicle development. The energy management problem of fuel cell hybrid electric vehicles is the key technology for power distribution. The traditional power following strategy has the advantage of a real-time operation but the power correction is usually based only on the state of charge of a lithium battery which causes the operating point of the fuel cell to be in the region of a low efficiency. To solve this problem this paper proposes a hybrid power-following-fuzzy control strategy where a fuzzy logic control strategy is used to optimise the correction module based on the power following strategy which regulates the state of charge while correcting the output power of the fuel cell towards the efficient operating point. The results of the joint simulation with Matlab + Advisor under the Globally Harmonised Light Vehicle Test Cycle Conditions show that the proposed strategy still ensures the advantages of real-time energy management and for the hydrogen fuel cell the hydrogen consumption is reduced by 13.5% and 4.1% compared with the power following strategy and the fuzzy logic control strategy and the average output power variability is reduced by 14.6% and 5.1% respectively which is important for improving the economy of the whole vehicle and prolonging the lifetime of fuel cell.

Decarbonising energy systems is a prevalent topic in the current literature on climate change mitigation but the additional climate burden caused by methane emissions along the natural gas value chain is rarely discussed at the system level. Considering a two-basket greenhouse gas neutrality objective (both CO2 and methane) we model cost-optimal European energy transition pathways towards 2050. Our analysis shows that adoption of best available methane abatement technologies can entail an 80% reduction in methane leakage limiting the additional environmental burden to 8% of direct CO2 emissions (vs. 35% today). We show that while renewable energy sources are key drivers of climate neutrality the role of natural gas strongly depends on actions to abate both associated CO2 and methane emissions. Moreover clean hydrogen (produced mainly from renewables) can replace natural gas in a substantial proportion of its end-uses satisfying nearly a quarter of final energy demand in a climate-neutral Europe.

Hydrogen fuel cell vehicles (HFCVs) are a promising technology for reducing vehicle emissions and improving energy efficiency. Due to the ongoing evolution of this technology there is limited comprehensive research and documentation regarding the energy modeling of HFCVs. To address this gap the paper develops a simple HFCV energy consumption model using new fuel cell efficiency estimation methods. Our HFCV energy model leverages real-time vehicle speed acceleration and roadway grade data to determine instantaneous power exertion for the computation of hydrogen fuel consumption battery energy usage and overall energy consumption. The results suggest that the model’s forecasts align well with real-world data demonstrating average error rates of 0.0% and −0.1% for fuel cell energy and total energy consumption across all four cycles. However it is observed that the error rate for the UDDS drive cycle can be as high as 13.1%. Moreover the study confirms the reliability of the proposed model through validation with independent data. The findings indicate that the model precisely predicts energy consumption with an error rate of 6.7% for fuel cell estimation and 0.2% for total energy estimation compared to empirical data. Furthermore the model is compared to FASTSim which was developed by the National Renewable Energy Laboratory (NREL) and the difference between the two models is found to be around 2.5%. Additionally instantaneous battery state of charge (SOC) predictions from the model closely match observed instantaneous SOC measurements highlighting the model’s effectiveness in estimating real-time changes in the battery SOC. The study investigates the energy impact of various intersection controls to assess the applicability of the proposed energy model. The proposed HFCV energy model offers a practical versatile alternative leveraging simplicity without compromising accuracy. Its simplified structure reduces computational requirements making it ideal for real-time applications smartphone apps in-vehicle systems and transportation simulation tools while maintaining accuracy and addressing limitations of more complex models.