Spain

The safest way to store hydrogen is in solid form physically entrapped in molecular form in highly porous materials or chemically bound in atomic form in hydrides. Among the different families of these compounds alkaline and alkaline earth metals alumino-hydrides (alanates) have been regarded as promising storing media and have been extensively studied since 1997 when Bogdanovic and Schwickardi reported that Ti-doped sodium alanate could be reversibly dehydrogenated under moderate conditions. In this review the preparative methods; the crystal structure; the physico-chemical and hydrogen absorption-desorption properties of the alanates of Li Na K Ca Mg Y Eu and Sr; and of some of the most interesting multi-cation alanates will be summarized and discussed. The most promising alanate-based reactive hydride composite (RHC) systems developed in the last few years will also be described and commented on concerning their hydrogen absorption and desorption performance.

This paper reviews previous research by the author in the field of hydrogen effects on progressively cold-drawn pearlitic steels in terms of hydrogen degradation (HD) hydrogen embrittlement (HE) or at the micro-level hydrogen-assisted micro-damage (HAMD) thus affecting their microstructural integrity and compromising the (macro-)structural integrity of civil engineering structures such as prestressed concrete bridges. It is seen that hydrogen effects in pearlitic microstructure (either oriented or not) are produced at the finest micro-level by plastic tearing in the form in general of hydrogen damage topography (HDT) with different appearances depending of the cold drawing degree evolving from the so-called tearing topography surface (TTS) in hot-rolled (not cold-drawn at all) or slightly cold-drawn pearlitic steels to a sort of enlarged and oriented TTS (EOTTS) in heavily drawn steels (the pronounced enlargement and marked orientation being along the wire axis or cold drawing direction). Whereas the pure TTS mode (null or low degree of cold drawing) resembles the Michelangello stone sculpture texture (MSST) the EOTTS mode does the same in relation to the Donatello wooden sculpture texture (DWST).

Electric vehicles are becoming more and more popular. One of the most promising possible solutions is one where a hybrid powertrain made up of a FC (Fuel Cell) and a battery is used. This type of vehicle offers great autonomy and high recharging speed which makes them ideal for many industrial applications. In this work three ways to build a hybrid power-train are presented and compared. To illustrate this the case of an industrial robot designed to move loads within a fully automated factory is used. The analysis and comparison are carried out through different objective criteria that indicate the power-train performance in different battery charge levels. The hybrid configurations are tested using real power profiles of the industrial robot. Finally simulation results show the performance of each hybrid configuration in terms of hydrogen consumption battery and FC degradation and dc bus voltage and current regulation.

Biogas is a renewable gas with low heat energy which makes it extremely difficult to use as fuel in conventional natural gas equipment. Nonetheless the use of hydrogen as a biogas additive has proven to have a beneficial effect on flame stability and combustion behavior. This study evaluates the biogas–hydrogen combustion in a conventional natural gas burner able to work up to 100 kW. Tests were performed for three different compositions of biogas: BG70 (30% CO₂) BG60 (40% CO₂) and BG50 (50% CO₂). To achieve better flame stability each biogas was enriched with hydrogen from 5% to 25%. The difficulty of burning biogas in conventional systems was proven as the burner does not ignite when the biogas composition contains more than 40% of CO₂. The best improvements were obtained at 5% hydrogen composition since the exhaust gas temperature and thus the enthalpy rises by 80% for BG70 and 65% for BG60. The stability map reveals that pure biogas combustion is unstable in BG70 and BG60; when the CO₂ content is 50% ignition is inhibited. The properties change slightly when the hydrogen concentrations are more than 20% in the fuel gas and do not necessarily improve.

The most profitable offshore energy resources are usually found away from the coast. Nevertheless the accessibility and grid integration in those areas are more complicated. To avoid this problematic large scale hydrogen production is being promoted for far offshore applications. The main objective of this paper is to analyze the ability of wave energy converters to maximize hydrogen production in hybrid wind and wave far offshore farms. To that end wind and wave resource data are obtained from ERA5 for different locations in the Atlantic ocean and a Maximum Covariance Analysis is proposed for the selection of the most representative locations. Furthermore the suitability of different sized wave energy converters for auxiliary hydrogen production in the far offshore wind farms is also analysed. On that account the hydrodynamic parameters of the oscillating bodies are obtained via simulations with a Boundary Element Method based code and their operation is modelled using the software tool Matlab. The combination of both methodologies enables to perform a realistic assessment of the contribution of the wave energy converters to the hydrogen generation of an hybrid energy farm especially during those periods when the wind turbines would be stopped due to the variability of the wind. The obtained results show a considerable hydrogen generation capacity of the wave energy converters up to 6.28% of the wind based generation which could remarkably improve the efficiency of the far offshore farm and bring important economical profit. Wave energy converters are observed to be most profitable in those farms with low covariance between wind and waves where the disconnection times of the wind turbines are prone to be more prolonged but the wave energy is still usable. In such cases a maximum of 101.12 h of equivalent rated production of the wind turbine has been calculated to be recovered by the wave energy converters.

Fossil fuels are being progressively substituted by a cleaner and more environmentally friendly form of energy where hydrogen fuel cells stand out. However the implementation of a competitive hydrogen economy still presents several challenges related to economic costs required infrastructures and environmental performance. In this context the objective of this work is to determine the environmental performance of the recovery of hydrogen from industrial waste gas streams to feed high-temperature proton exchange membrane fuel cells for stationary applications. The life-cycle assessment (LCA) analyzed alternative scenarios with different process configurations considering as functional unit 1 kg of hydrogen produced 1 kWh of energy obtained and 1 kg of inlet flow. The results make the recovery of hydrogen from waste streams environmentally preferable over alternative processes like methane reforming or coal gasification. The production of the fuel cell device resulted in high contributions in the abiotic depletion potential and acidification potential mainly due to the presence of platinum metal in the anode and cathode. The design and operation conditions that defined a more favorable scenario are the availability of a pressurized waste gas stream the use of photovoltaic electricity and the implementation of an energy recovery system for the residual methane stream.

The study of the viability of hydrogen production as a sustainable energy source is a current challenge to satisfy the great world energy demand. There are several techniques to produce hydrogen either mature or under development. The election of the hydrogen production method will have a high impact on practical sustainability of the hydrogen economy. An important profile for the viability of a process is the calculation of energy and exergy efficiencies as well as their overall integration into the circular economy. To carry out theoretical energy and exergy analyses we have estimated proposed hydrogen production using different software (DWSIM and MATLAB) and reference conditions. The analysis consolidates methane reforming or auto-thermal reforming as the viable technologies at the present state of the art with reasonable energy and exergy efficiencies but pending on the impact of environmental constraints as CO2 emission countermeasures. However natural gas or electrolysis show very promising results and should be advanced in their technological and maturity scaling. Electrolysis shows a very good exergy efficiency due to the fact that electricity itself is a high exergy source. Pyrolysis exergy loses are mostly in the form of solid carbon material which has a very high integration potential into the hydrogen economy.

The way to decarbonization will be characterized by the huge production of hydrogen through sustainable routes. Thus the basic production way is water electrolysis sustained by renewable energy sources allowing for obtaining “green hydrogen”. The present paper reviews the main available technologies for the water electrolysis finalized to the hydrogen production. We describe the fundamental of water electrolysis and the problems related to purification and/or desalinization of water before electrolysis. As a matter of fact we describe the energy efficiency issues with particular attention to the potential application in the steel industry. The fundamental aspects related to the choice of high-temperature or low-temperature technologies are analyzed.

The use of low carbon fuels (LCFs) in internal combustion engines is a promising alternative to reduce pollution while achieving high performance through the conversion of the high energy content of the fuels into mechanical energy. However optimizing the engine design requires deep knowledge of the complex phenomena involved in combustion that depend on the operating conditions and the fuel employed. In this work computational fluid dynamics (CFD) simulation tools have been used to get insight into the performance of a Volkswagen Polo 1.4L port-fuel injection spark ignition engine that has been fueled with three different LCFs coke oven gas (COG) a gaseous by-product of coke manufacture H2 and CH4. The comparison is made in terms of power pressure temperature heat release flame growth speed emissions and volumetric efficiency. Simulations in Ansys® Forte® were validated with experiments at the same operating conditions with optimal spark advance wide open throttle a wide range of engine speed (2000–5000 rpm) and air-fuel ratio (λ) between 1 and 2. A sensitivity analysis of spark timing has been added to assess its impact on combustion variables. COG with intermediate flame growth speed produced the greatest power values but with lower pressure and temperature values at λ = 1.5 reducing the emissions of NO and the wall heat transfer. The useful energy released with COG was up to 16.5% and 5.1% higher than CH4 and H2 respectively. At richer and leaner mixtures (λ = 1 and λ = 2) similar performances were obtained compared to CH4 and H2 combining advantages of both pure fuels and widening the λ operation range without abnormal combustion. Therefore suitable management of the operating conditions maximizes the conversion of the waste stream fuel energy into useful energy while limiting emissions.

This research work presents an artificial intelligence approach to predicting the hydrogen concentration in the producer gas from biomass gasification. An experimental gasification plant consisting of an air-blown downdraft fixed-bed gasifier fueled with exhausted olive pomace pellets and a producer gas conditioning unit was used to collect the whole dataset. During an extensive experimental campaign the producer gas volumetric composition was measured and recorded with a portable syngas analyzer at a constant time step of 10 seconds. The resulting dataset comprises nearly 75 hours of plant operation in total. A hybrid intelligent model was developed with the aim of performing fault detection in measuring the hydrogen concentration in the producer gas and still provide reliable values in the event of malfunction. The best performing hybrid model comprises six local internal submodels that combine artificial neural networks and support vector machines for regression. The results are remarkably satisfactory with a mean absolute prediction error of only 0.134% by volume. Accordingly the developed model could be used as a virtual sensor to support or even avoid the need for a real sensor that is specific for measuring the hydrogen concentration in the producer gas.