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In order to ensure the safety of hydrogen refueling systems and fuel cell vehicles under various filling conditions, the filling parameters are usually set very conservatively, leading to waste energy consumption and investment. The lumped parameter hydrogen gas model and one-dimension tank wall model of the hydrogen filling process previously proposed by our team were extended and improved to the entire hydrogen refueling system by considering the Joule-Thomson effect, kinetic energy and using a more accurate model of the heat transfer coefficients between the inner tank wall and hydrogen gas and between the outer tank wall and ambient. Based on our validated model, the effects of constant and two-stage average pressure ramp rates (APRRs) and precooling/inlet temperatures on refueling performances were investigated, respectively. Compared with the optimal filling strategy of the reference paper, where a constant APRR is the best, our two-stage APRRs can further reduce the cooling power for various inlet temperatures without increasing the cooling energy. For example, maximum cooling power can be reduced by 23.8% at the inlet temperature of −20 °C. Compared with the previous research result obtained using a constant inlet temperature solved by the analytical solution, the two-stage inlet temperatures can further reduce the cooling power by 16.3% at an APRR of 0.428 MPa/s without increasing the cooling energy. • A thermodynamic model for a hydrogen refueling system is improved and well validated. • Joule-Thomson effect, kinetic energy and accurate heat transfer model are considered. • Effects of two-stage average pressure ramp rates and inlet temperatures are studied. • Two-stage strategies can reduce cooling power without increasing cooling energy. [ABSTRACT FROM AUTHOR]

This paper presents a novel energy management strategy (EMS) to control a wind-hydrogen microgrid which includes a wind turbine paired with a hydrogen-based energy storage system (HESS), i.e., hydrogen production, storage and re-electrification facilities, and a local load. This complies with the mini-grid use case as per the IEA-HIA Task 24 Final Report, where three different use cases and configurations of wind farms paired with HESS are proposed in order to promote the integration of wind energy into the grid. Hydrogen production surpluses by wind generation are stored and used to provide a demand-side management solution for energy supply to the local and contractual loads, both in the grid-islanded and connected modes, with corresponding different control objectives. The EMS is based on a hierarchical model predictive control (MPC) in which long-term and short-term operations are addressed. The long-term operations are managed by a high-level MPC, in which power production by wind generation and load demand forecasts are considered in combination with day-ahead market participation. Accordingly, the hydrogen production and re-electrification are scheduled so as to jointly track the load demand, maximize the revenue through electricity market participation and minimize the HESS operating costs. Instead, the management of the short-term operations is entrusted to a low-level MPC, which compensates for any deviations of the actual conditions from the forecasts and refines the power production so as to address the real-time market participation and the short time-scale equipment dynamics and constraints. Both levels also take into account operation requirements and devices' operating ranges through appropriate constraints. The mathematical modeling relies on the mixed-logic dynamic (MLD) framework so that the various logic states and corresponding continuous dynamics of the HESS are considered. This results in a mixed-integer linear program which is solved numerically. The effectiveness of the controller is analyzed by simulations which are carried out using wind forecasts and spot prices of a wind farm in center-south of Italy. • Design of control algorithms for islanded and grid-connected microgrids. • Development of hierarchical MPCs to target long-term and short-term operations. • Tracking the load demand and maximizing the revenue via electricity markets. • Minimization of the HESS operational costs. [ABSTRACT FROM AUTHOR]

The number of hydrogen refuelling stations worldwide has increased to over 700 due to the rapid development of green hydrogen energy. The risk assessment of hydrogen refuelling stations is indispensable to prevent accidents, and its foundation is accident scenarios screening. Although the integrated energy supply station containing fuels such as hydrogen, compressed natural gas (CNG), methanol eliminates the need for building hydrogen refuelling stations separately, the risk assessment for these complex systems has not been comprehensively studied. This paper proposes a scenario screening approach for identifying potential hazards in multi-fuel integrated energy supply stations. The risk of the processing unit was evaluated, and the leakage scenarios were pre-screened to identify credible leakage scenarios that adhere to the principle of maximum credibility by considering the frequency of occurrence and severity of consequences in two parts. Based upon acquired credible leakage scenarios, secondary screening of possible accident consequences was conducted by calculating the value of the credible factor to obtain the final maximum credible accident scenarios (MAS). Credible factors are derived from the accident probability, consequence severity, population density and asset density. By comparing the values of the credible factors, the accident scenarios with a low probability or low severity were eliminated, and the accident scenarios with the highest credible factors of each unit were retained as the MAS that require further consequence simulation analysis. The results offer a crucial foundation for the consequences and risk assessment of integrated energy supply stations. • Potential consequences of accidents caused by hydrogen and other fuel leaks. • Credible scenarios for fuel leaks are identified. • Maximum credible accident scenarios are determined. • Hydrogen compressor and associated piping are most susceptible to jet fires and explosions. [ABSTRACT FROM AUTHOR]

The transition to a low-carbon energy system can be depicted as a "great reconfiguration" from a socio-technical perspective that carries the risk of impact shifts. Electrification with the objective of achieving rapidly deep decarbonisation must be accompanied by effective efficiency and flexibility measures. Hydrogen can be a preferred option in the decarbonisation process where electrification of end-uses is difficult or impractical as well as for long-term storage in energy infrastructure characterised by a large penetration of renewable energy sources. Notwithstanding the current uncertainties regarding costs, environmental impact and the inherent difficulties of increasing rapidly supply capacity, hydrogen can represent a solution to be used in multi-energy systems with combined heat and power (CHP), in particular in urban energy districts. In fact, while achieving carbon savings with natural gas fuelled CHP is not possible when low grid carbon intensity factors are present, it may still be possible to use it to provide flexibility services and to reduce emissions further with switch from natural gas to hydrogen. In this paper, a commercially established urban district energy scheme located in Southampton (United Kingdom) is analysed with the goal of exploring potential variations in its energy demand. The study proposes the use of scalable data-driven methods and probabilistic simulation to generate seasonal energy demand patterns representing the potential short-term and long-term evolution of the energy district. • Hydrogen role in the transition to low carbon energy systems for urban energy district. • Data-driven urban energy modelling using regression-based approaches. • Probabilistic modelling of energy demand in terms of electricity and fuels. • Climate change impact and energy efficiency measures accounting. • Seasonal variations of energy demand patterns from short-term to long-term scenarios. [ABSTRACT FROM AUTHOR]

In recent years, sustainable development has become a challenge for many societies due to natural or other disruptive events, which have disrupted economic, environmental, and energy infrastructure growth. Developing hydrogen energy infrastructure is crucial for sustainable development because of its numerous benefits over conventional energy sources. However, the complexity of hydrogen energy infrastructure, including production, utilization, and storage stages, requires accounting for potential vulnerabilities. Therefore, resilience needs to be considered along with sustainable development. This paper proposes a decision-making framework to evaluate the resilience of hydrogen energy infrastructure by integrating resilience indicators and sustainability contributing factors. A holistic taxonomy of resilience performance is first developed, followed by a qualitative resilience assessment framework using a novel Intuitionistic fuzzy Weighted Influence Nonlinear Gauge System (IFWINGS). The results highlighted that Regulation and legislation, Government preparation, and Crisis response budget are the most critical resilience indicators in the understudy hydrogen energy infrastructure. A comparative case study demonstrates the practicality, capability, and effectiveness of the proposed approach. The results suggest that the proposed model can be used for resilience assessment in other areas. • A Holistic taxonomy of resilience is proposed for hydrogen infrastructure. • A Novel IFWINGS is proposed for advanced qualitative resilience assessment. • Importance of regulation, government preparation, and crisis response budget are discussed. • A Practical and effective application on a real hybrid wind-hydrogen power plant is presented. • Framework provides a tool for promoting sustainable development. [ABSTRACT FROM AUTHOR]

After a natural disaster, electrical grids might go into a self-healing mode to restore service and reconnect any customers that lost power. In the self-heal system, the fast operation and restoring the critical loads (CLs) during a fault by available resources can increase the flexibility and resilience of the network. In addition to renewable energy sources and electric vehicles (EVs) storage devices, the hydrogen storage system and the process of converting hydrogen into electric energy by micro-gas turbine (MGT) have been modeled in order to assess the impact of this storage system in electrical loads restoration in critical conditions. Self-healing functionality is enhanced by using alternative and novel energy sources. In such a situation, how to interact with the stochastic nature of network components will be challenging. This paper formulates the optimal service restoration (SR) problem using chance-constrained Adaptive Distributionally Robust Optimization (ADRO) to address the ambiguities introduced by the uncertain parameters. A tri-level robust optimization model is developed such that the optimal switching in the network until clearing the fault is determined at the upper level, and the maximization of the SR based on the load demand values is determined at the lower level. The proposed method is demonstrated by simulation results on the modified Civanlar test system. In an equal operating condition and considering β = 3, it can be seen that the initial hydrogen State of the Tank (SoT) by 50 % can improve the load restoration by 7.5 % compared to the uncharged hydrogen tank. By increasing the initial SoT to the nominal value (10 Kg), the load restoration can increase to 13.2 %. [Display omitted] • Customized hydrogen into electric energy conversion model is developed in the energy management field. • Each uncertain parameter is considered ambiguous in the manner that follows an unknown but bounded distribution. • EVs, PHEVs, flexible loads, and the coordinated operation of the hydrogen-to-power system are all taken into account simultaneously. • A tri-level MILP model is formulated to determine the service restoration schedule. • CVaR is employed to effectively deal with the uncertainty of the parameters. [ABSTRACT FROM AUTHOR]

The increasing heterogeneity and scalability of the Internet of everything, especially, the Energy Internet (EI), is a prompt for novel engineering paradigms. The current infrastructure of hardware technologies besides the available software stack is becoming obsolete for handling the advanced requirements of the smart energy ecosystem. Accordingly, software definitions of the Internet of Things (IoT) stack functions are gaining interest to provide more flexible and scalable implementations. This paper investigates a sophisticated softwarization explicit hybrid model predictive control strategy for energy storage facility systems through the accessor design pattern. This strategy is presumed to support and facilitate the integration of higher-level analytic and control functionalities within the IoT stack at edges and nodes. Simulation is conducted with the Ptolemy II software to evaluate the execution semantics of the proposed strategy. In addition, real-time experiments on a lab-scale hydraulic tank process with both abrupt and gradual commands test scenarios showed the efficiency and reliability of the accessor-based controllers for achieving the control objectives for the benchmark storage facility with an abstract implementation. The analysis shows that this process can serve as a benchmark to mimic the charge and discharge cycles of storage elements in EI ecosystems. • A new paradigm for hydrogen energy storage interfacing within energy Internet ecosystems is proposed and investigated. • An actor-oriented approach is applied for implementing real-time control systems of hydrogen storage. • Software-defined model predictive control is implemented within a Node.js accessor host. • A benchmark process is developed as an emulator for hydrogen energy storage to evaluate the accessors design pattern. [ABSTRACT FROM AUTHOR]

In this paper we investigate the nature of hydrogen diffusion in substoichiometric TiC using simulations. Specifically, we examine how well connected the carbon structural vacancies are in TiC x using percolation theory and how many structural carbon vacancies are connected to the surface of TiC x. This provides direct insight into the number of sites available for hydrogen storage and the interconnected nature of the carbon vacancy network. We also compute the binding energies and migration energies of hydrogen in TiC x using density functional theory. This is conducted over a range of carbon concentrations from nearly stoichiometric TiC to Ti 2 C and includes the differences in vacancy ordering. We find that the migration energy of hydrogen in TiC x generally decreases with carbon loss and is associated with the tetrahedral interstices near them but that the binding energy of hydrogen to TiC x is independent of carbon concentration. Furthermore, we show that this migration path can occur through the tetrahedral interstices, which is influenced by local carbon concentration. These results also demonstrate the vacancy ordered R 3 ¯ m Ti 2 C structure does not possess any more superior ability to store or transport hydrogen than the F d 3 ¯ m Ti 2 C structure. • Hydrogen insertion in TiC x should occur for carbon concentrations below TiC 0.7. • The energy barriers for hydrogen diffusion drop with carbon concentration. • Hydrogen diffusion occurs from carbon vacancy to tetrahedral interstice. • It is easier to diffuse hydrogen into ordered F d 3 ¯ m Ti 2 C than R 3 ¯ m Ti 2 C. [ABSTRACT FROM AUTHOR]

There are complex coupling relationships between flight motion and energy management for hybrid electric fixed wing UAVs with photovoltaic/fuel cell/battery. Aiming at realizing high-energy-efficiency long endurance autonomous flight, this paper proposes a coordinated optimization method of trajectory optimization and energy management for hybrid electric UAVs. Numerical simulation and experiment are carried out. Separated by surplus demand energy except that produced by PV, this method includes an optimal energy flight trajectory optimization layer and an energy management layer. For the former, fuzzy neural network sequential convex optimization (FNNSCP) is proposed to handle the flight trajectory optimization problem for maximizing utilization solar energy. For the latter, an online energy management strategy based on convex quadratic programming MPC (CQPMPC) is proposed to realize the power allocation. Numerical simulation results show that FNNSCP reduced 2% energy requirement compared with Radau pseudo-spectral method (RPM) from flight trajectory optimization level. From energy management level, CQPMPC saves hydrogen consumption by 3.1% and 16.3% compared with nonlinear model predictive control (NMPC) and fuzzy logic state machine (FLSM), respectively. In the experiment, less hydrogen fuel is consumed by proposed method by 5.2% and 15.6% compared with NMPC and FLSM, respectively. Experimental results show that the proposed method has better energy-saving performance and excellent real time performance. It indicates that optimizing flight trajectory and improving energy management efficiency can realize the high-energy-efficiency flight of hybrid electric UAVs. This method is conducive to promoting the application of hydrogen energy in the field of UAVs. [Display omitted] • A coordinated optimization method is proposed for the high-energy-efficiency flight. • Fuzzy neural network adaptive sequential convex optimization method is proposed. • Online energy management strategy with convex quadratic programming MPC is proposed. • The proposed method is verified by simulation and energy management experiment. [ABSTRACT FROM AUTHOR]

The transition from fossil fuels to renewable energy sources is seen as an essential step toward a more sustainable future. Hydrogen is being recognized as a promising renewable energy carrier to address the intermittency issues associated with renewable energy sources. For hydrogen to become the "ideal" low or zero-carbon energy carrier, its storage and transportation shortcomings must be addressed. This paper will provide the current large-scale green hydrogen storage and transportation technologies, including ongoing worldwide projects and policy direction, an assessment of the different storage and transportation methods (compressed hydrogen storage, liquid hydrogen, blending hydrogen into natural gas pipelines, and ammonia as green hydrogen carrier), as well as economic factors that influence the viability of large-scale green hydrogen storage and transportation. The results of our study highlight several significant findings concerning the cost, challenges, and potential advancements in the green hydrogen storage and transportation field. Our analysis demonstrates that the cost associated with storing and transporting green hydrogen is anticipated to decrease over time due to technological advancements and economies of scale being achieved. However, the commercialization of this technology requires addressing challenges related to storage methods, transportation modes, efficiency optimization, and technology adoption. For example, our research highlights the need for thorough technical and economic evaluations of using salt caverns for hydrogen storage. The efficiency of hydrogen storage and transportation utilizing existing infrastructure, such as storage tanks and natural gas pipelines. By elucidating these aspects, our research contributes valuable insights that can guide future endeavors toward achieving a sustainable and economically viable green hydrogen industry. • Role of government support in green hydrogen storage remains crucial. • Different storage and transportation methods is analyzed and compared. • Cost of hydrogen is expected to decrease for economies of scale. [ABSTRACT FROM AUTHOR]

Owing to contamination of air and environmental hazards, the demand for sustainable fuels in power plants and other heat engines has climbed undeniably. Aluminum metal is classified among high energy density and low carbon content, which can be reacted with water and repeatedly released a large amount of heat and hydrogen. Since hydrogen is one of the zero-carbon and clean fuels, aluminum can be exploited as a promising energy-carrying and renewable source of energy. This paper is dedicated to the customization of two novel schemes of the combined cycle of power generation systems. The main components of the proposed integrated installations include a hydrogen turbine, gas turbine, multi pressure steam turbines, condenser, heat recovery steam generator and aluminum-water reactor, in which pressurized water absorbs produced heat of the reactor then superheated steam expands in steam turbines. Direct supplied hydrogen, which is generated from the Al-water reaction, expands in the hydrogen turbine and subsequently burns in the combustion chamber of the gas turbine. Hydrogen properties, consumed heat of reactor, generated powers, effects of streams pressure, energetic and exergetic productivity variation of both schemes were evaluated comparatively to ensure the best system performance along with the high net efficiency. According to the numerical analysis of the thermodynamic characteristics in steady state regime using EES software, the energy and energy efficiencies of scheme A were calculated to be 40.72% and 38.36%, besides in scheme B were 39.6% and 37.3%, respectively. [Display omitted] • Demands for environmentally friendly fuels have been raised exponentially. • Aluminum water reaction can release repeatedly heat and hydrogen. • Hydrogen as zero-carbon fuel burns in combustion chamber. • Stream of steam can absorb produced heat in Al-water reaction. • Performance of reheat cycle is better than cycle without reheat. [ABSTRACT FROM AUTHOR]

In this paper, wind resource availability was determined by analyzing the meteorological wind energy potential at the hub height of wind turbines. The wind resource potential was identified in specific geographic locations. Technical factors, such as siting requirements and resource availability, were taken into account in the investigation. The economic potential was calculated for each area of Algeria, considering overall losses. Subsequently, the potential for reducing fossil fuel usage was determined through wind to hydrogen estimation. The main components utilized in this work were a Vestas-90 wind turbine (V90–2.0 MW) and an alkaline electrolyzer. The analysis employed a Geographical Information System (GIS) tool. The results demonstrate Algeria's significant potential for wind to hydrogen production, estimated at 1.093 Gt/year without constraints, and reduced to 1.066 Gt/year when considering constraints. The levelized cost of wind to hydrogen production in Algeria varies between 1.51 and 15.37 US $/kg, depending on the chosen wind turbine. The wind to hydrogen production potential identified has the capacity to replace the entire current fossil fuel consumption in the transportation sector, which amounts to 5.28 Mt H 2 /year. The utilization of wind to hydrogen in the transport sector results in a significant reduction of CO 2 emissions, with a calculated avoidance of 45.69 Mt compared to the use of gasoline and diesel. Hydrogen produced from wind energy resources also could be used to support other sectors, including residential, agricultural, and industry in Algeria. • GIS-Based approach is used to evaluate the potential for wind to hydrogen production in Algeria. • The total wind to hydrogen potential in Algeria, when considering constraints, is estimated at 1.066 Gt/year, covering an area of 730,719 km2. • The levelized cost of wind to hydrogen production in Algeria ranges between 1.51 and 15.37 US $/kg, depending on the selected wind turbine (V90–2.0 MW). • The CO 2 emissions avoided in the transport sector are 45.69 Mt compared if the same amount of gasoline and diesel used. [ABSTRACT FROM AUTHOR]

With the rise of the hydrogen energy industry, countries worldwide have introduced relevant policies to elevate the development of the hydrogen energy industry to the height of national energy strategy, and hydrogen energy will become a significant factor affecting the future industrial structure and national competitiveness. The path of technology evolution can trace the history of technology development and predict the trend of technology development, which can help to grasp the first opportunity of technological innovation and lead the direction of technological development. However, there are fewer studies on technology evolution in hydrogen energy. The existing studies mainly use bibliometrics to mine a single technology, and the studies using text mining suffer from the defect that keywords are difficult to decipher. Given this, this paper conducts research on identifying the technology evolution path in the field of hydrogen energy, adopts text mining methods to mine patent data, and introduces document vectorization and phrase mining algorithms to improve the mining depth while increasing the interpretability of the results. It is found that the hydrogen energy industry is in a period of rapid development; the succession and integration of hydrogen energy technologies are good, and the technological development trend focuses on hydrogen storage materials, hydrogen fuel cell vehicles, and green hydrogen preparation. • Identify the mesh evolution path of hydrogen energy technology using text mining. • Introduce a phrase-mining algorithm to make interpreting the results easier. • Analyze the overall development trend of hydrogen energy technology. • Explore the technological themes and evolution patterns in the field of hydrogen energy. [ABSTRACT FROM AUTHOR]

This paper presents a study to optimize biogas feed distribution ratio between the reformer and the burner for hydrogen production. The objective is to improve operational and economic efficiency by optimizing the process and minimizing calorific deficits due to CO 2 in direct biogas reforming. The results showed that increasing burner distribution ratio increased energy demand, and decreasing the reformer distribution ratio decreased the energy conversion efficiency. Therefore, an optimized distribution ratio is important. Computational fluid dynamics analysis and experimental investigations show that a 5:5 feed distribution at temperatures above 750 °C facilitates efficient heat transfer to the outer wall of the reforming tube. We believe that this study highlights the importance of optimizing combustion energy and hydrogen production through the distribution ratio while ensuring temperature uniformity in the reformer. • Direct biogas reforming is a way to reduce process costs. • Optimized biogas ratio is vital for efficient H 2 production and minimal heat loss. • Decreasing reformer distribution ratio lowers energy conversion efficiency. • 5:5 feed distribution at 750 °C is ideal for heat transfer in reforming gas. • Study contributes to design and operation of biogas-fed hydrogen production systems. [ABSTRACT FROM AUTHOR]

Hydrogen fuel has shown promise as a clean, alternative fuel aiding in the reduction of fossil fuel dependence within the transportation sector. However, hydrogen refueling stations and infrastructure remains a barrier and are a prerequisite for consumer adoption of low-cost and low-emission fuel cell electric vehicles (FCEVs). The costs for FCEV fueling include both station capital costs and operation and maintenance (O&M) costs. Contributing to these O&M costs, unscheduled maintenance is presently more costly and more frequent than for similar gasoline fueling infrastructure and is asserted to be a limiting factor in achieving FCEV customer acceptance and cost parity. Unscheduled maintenance leads to longer station downtime, therefore, causing an increase in missed fueling opportunities, which forces customers to seek refueling at other operable stations that may be significantly farther away. This research proposes a framework for a hydrogen station prognostics health monitoring (H2S PHM) model that can minimize unexpected downtime by predicting the remaining useful life for primary hydrogen station components within the major station subsystems. The H2S PHM model is a data-driven statistical model, based on O&M data collected from 34 retail hydrogen stations located in the U.S. The primary subcomponents studied are the dispenser, compressor, and chiller. The remaining useful life calculations are used to decide whether or not maintenance should be completed based on the prediction and expected future station use. This paper presents the background, method, and results for the H2S PHM model as for a means for improving station availability and customer confidence in FCEVs and hydrogen infrastructure. • Hydrogen station reliability is a key contributor to market success. • Mean fills between failure and station availability are lower than conventional technologies. • A prognostics health monitoring system can improve hydrogen station availability. • Estimated remaining useful life of primary components assists in maintenance decisions. [ABSTRACT FROM AUTHOR]

The safety of hydrogen directly affects the use of hydrogen refueling stations and public acceptance of hydrogen energy. This paper presented a methodology for the optimal design of the minimum height, width, and safety distance of the firewall of the hydrogen refueling station under various leakage pressures. The obtained relationship between distances and different hydrogen storage pressures is essential for directing the design of hydrogen refueling stations and firefighters to carry out the rescue. Results from numerical simulation showed that the firewall should be 2 m taller than the leakage hole to prevent the hydrogen jet fire from spreading back. The distance before and behind the firewall presented a linear relationship with the leakage pressure. The specific safe distances behind the firewall were 8.4, 8.5, 9.2, and 9.3 m. The firewall width exhibited a non-linear relationship with the leakage pressure. The specific values were 2.5 m for 35 or 45 MPa and 3 m for 70 or 90 MPa. • Methodology for the optimal design of firewalls in hydrogen refueling stations is determined. • The firewall should be 2 m higher than the leakage hole. • Firewalls can deflect flames and prevent them from spreading behind walls. • The distance before and behind the firewall increases with the increase of hydrogen storage pressures. [ABSTRACT FROM AUTHOR]

In this paper, a novel stochastic risk-averse mixed-integer linear programming (MILP) model is developed for optimal electricity procurement of hydrogen fuel stations (HFSs) with responsive hydrogen demands. In the developed model, HFS operator may procure its required electricity through day-ahead (DA) market, bilateral contracts, a contract with withdrawal penalty (CWP) and balancing market. The HFS is committed to inject a pre-specified volume of hydrogen into a natural gas network. In the developed stochastic model, the uncertainties in hydrogen demand and DA market prices are characterized as random variables and modeled as scenarios. The developed model is a two-stage model in which the decisions on transactions with bilateral contracts are the first-stage decision variables and the other decision variables belong to the second stage. The risk of suffering from high procurement costs is modeled using the Conditional Value at Risk (CVaR). The results confirm the efficiency of the proposed model both in terms of reduction in HFS expected cost and risk alleviation. The results show that the transaction through bilateral contracts decreases the expected cost and CVaR respectively by 6% and 3%. The results also indicate that the participation in the balancing market decreases the expected cost and CVaR respectively by 6% and 1.6%. As per results, in scenarios in which DA market prices are lower than CWP prices, HFS operator prefers to pay a penalty fee and withdraw from CWP. The sensitivity of HFS profit to the weight factor of risk metric and the participation factor of responsive demands are assessed. [Display omitted] • A model is developed for electricity procurement of hydrogen fuel stations (HFSs). • The uncertainties in demands and market prices are considered. • HFS procures electricity by day-ahead and balancing market and bilateral contracts. • Impact of different markets and transactions on HFS profit is assessed. • Sensitivity of HFS profit to weight of risk metric is assessed. [ABSTRACT FROM AUTHOR]

The real-time perception of the combustion flow of a scramjet can help to quickly evaluate the working state and provide a new opportunity for the intelligent reconstruction of the data-driven combustion flow field. However, the working process of supersonic combustors is extremely short, usually of the order of milliseconds, and the inference speed is slow due to the large number of parameters of traditional deep learning flow field reconstruction models within a very short time. Currently, knowledge distillation is known as an effective model compression method. In this paper, a neural network model based on symmetric structure cascade (NNSSC1) is proposed. By means of symmetric structure cascade, features of different levels are spliced and fused, which can effectively improve the reconstruction performance of the model. Secondly, to accelerate the application of the neural network model in the flight test, a student model with a simple structure is constructed. By distillation learning, the NNSSC model is used as the teacher model, combining the high performance of the teacher model and the high efficiency of the student model, and the combustion flow field is reconstructed with high speed and high precision based on the supersonic combustor wall pressure. In a direct connected supersonic pulse combustion wind tunnel with an inflowing Mach number of 2.5, the model was trained and tested on a dataset constructed in a hydrogen fuel scramjet experiment with different equivalent ratios. This method achieves high-precision and efficient reconstruction of complex flow fields in the combustor based on sparse wall pressure, providing more reliable data for accurately evaluating the flow and combustion status of the combustor of a scramjet. • 1、A model compression method for supersonic flow field reconstruction is presented. • 2、A cascade neural network model with symmetric structure is presented. • 3、Shock wave can be predicted quickly and accurately based on wall pressure. • 4、Flow field reconstruction model of knowledge distillation learning is innovatively proposed. [ABSTRACT FROM AUTHOR]

Hydrogen, as a carbon-free energy carrier, has emerged as a crucial component in the decarbonization of the energy system, serving as both an energy storage option and fuel for dispatchable power generation to mitigate the intermittent nature of renewable energy sources. However, the unique physical and combustion characteristics of hydrogen, which differ from conventional gaseous fuels such as biogas and natural gas, present new challenges that must be addressed. To fully integrate hydrogen as an energy carrier in the energy system, the development of low-emission and highly reliable technologies capable of handling hydrogen combustion is imperative. This study presents a ground-breaking achievement - the first successful test of a micro gas turbine running on 100% hydrogen with NOx emissions below the standard limits. Furthermore, the combustor of the micro gas turbine demonstrates exceptional fuel flexibility, allowing for the use of various blends of hydrogen, biogas, and natural gas, covering a wide range of heating values. In addition to a comprehensive presentation of the test rig and its instrumentation, this paper illuminates the challenges of hydrogen combustion and offers real-world operational data from engine operation with 100% hydrogen and its blends with methane. • Hydrogen's potential as an alternative, carbon-free fuel for micro gas turbines is assessed. • The obstacles of utilizing hydrogen fuel in a micro gas turbine are addressed and the necessary modifications are presented. • Data from successful tests of a micro gas turbine running on hydrogen blends ranging up to 100% hydrogen is presented. • NOx emissions below the standard limits were achieved with the new setup. • The study's outcomes could aid researchers and developers in incorporating hydrogen as a carbon-free energy carrier. [ABSTRACT FROM AUTHOR]

This paper investigates laminar premixed hydrogen/air flame-wall interactions (FWI) subject to flame stretch (curvature and strain rate). Direct numerical simulations of finite-rate chemical reactions and in-depth molecular diffusion are used to numerically study two-dimensional (2D) V-shaped flames, with one side functioning as an isothermal cold wall that interacts with the flame and the other as a symmetrical center for free-propagating flame. An isometric grid with a grid resolution of 10 μm is used to resolve the FWI zone. It is discovered that the wall at the flame tip experiences increased negative stretching and enhanced local preferential diffusion which reduces the intensity of local combustion. This effect is especially noticeable at low equivalent ratios. Additionally, there is a close relationship between quenching behavior and flame dynamics. The present results show that the Markstein numbers for both the sidewall quenching flame and the freely propagating flame (Ma SWQ and Ma FF) are negative in lean hydrogen flames and positive in rich hydrogen flames. Cold wall has less impact on Ma. Furthermore, an intersection in the equivalence ratio is observed in the lean-fuel hydrogen/air flame, located at Φ = 0.8–1.0, with a change in the sign of Ma. • Resolved simulation of steady flame-wall interaction of hydrogen flames over a wide range of equivalent ratios. • Analysis of the V-shaped flame with/without wall from a thermodynamics perspective. • The wall increased negative flame stretching and enhanced local preferential diffusion. • Comparison of Markstein numbers between sidewall quenching flames and free propagating flames. • A crossover of equivalence ratio was observed in fuel poor hydrogen/air flames. [ABSTRACT FROM AUTHOR]