Production & Supply Chain

The present study explores the potential of integrating the NET Zero Cycle (NZC) with hydrogen production by alkaline electrolyzers. To achieve this an Aspen Plus model was developed for the NZC and its accuracy was first confirmed by comparing it with literature data. The creation of a model for an alkaline electrolyzer was achieved using Aspen Custom Modeler and later imported into Aspen Plus. A comprehensive simulation was conducted in Aspen Plus to examine the synergies between the NZC and the alkaline electrolyzer. In this integration the oxygen demand of the NZC is met by a combination of an air separation unit (ASU) and the electrolyzer. The electrolyzer not only partially fulfills the oxygen requirements but also acts as an external heat supplier for the regenerator. Additionally the NZC supplies deionized water to the electrolyzer. A thermodynamic analysis in dicates that the integration of the NZC and alkaline electrolyzers results in a higher efficiency of 56.5 % compared to the stand-alone NZC an improvement of 2.3 %. Assuming that the NZC and alkaline electrolyzer operate at the same power production and input levels the alkaline electrolyzer can generate substantial oxygen to reduce the energy consumption of the ASU significantly. This aspect represents one of the primary reasons for the enhanced efficiency observed in this study. However the ASU still needs to be operated to provide the full oxygen demands of the process. To identify the key parameters influencing the integration of the NZC and alkaline electrolyzers a sensitivity analysis was performed. To enhance the system efficiency a comprehensive investigation was conducted to analyze the influence of key parameters such as combustor outlet temperature (COT) turbine outlet pressure (TOP) and combustor outlet pressure (COP) on the thermodynamic first law efficiency of the cycle. An increase in electrolyzer input power and a reduction in electrolyzer inlet feed were associated with a higher cycle effi ciency. The results also highlight that the TOP COT and the electrolyzer input power have a more significant impact on the cycle thermodynamic first law efficiency within the range of 5.7 4.0 and 2.6 % respectively while COP only causes a 0.4 % change in cycle efficiency. The integrated system demonstrates an impressive system first law thermodynamic efficiency of 62.5 % and exergy efficiency of 60.6 %.

Studies estimating the production cost of hydrogen-based fuels known as e-fuels often use renewable power profile time series obtained from open-source simulation tools that rely on meteorological reanalysis and satellite data such as Renewables.ninja or PVGIS. These simulated time series contain errors compared to real on-site measured data which are reflected in e-fuels cost estimates plant design and operational performance increasing the risk of inaccurate plant design and business models. Focusing on solar-powered e-fuels this study aims to quantify these errors using high-quality on-site power production data. A state-of-the-art optimization techno-economic model was used to estimate e-fuel production costs by utilizing either simulated or high-quality measured PV power profiles across four sites with different climates. The results indicate that in cloudy climates relying on simulated data instead of measured data can lead to an underestimation of the fuel production costs by 36 % for a hydrogen user requiring a constant supply considering an original error of 1.2 % in the annual average capacity factor. The cost underestimation can reach 25 % for a hydrogen user operating between 40 % and 100 % load and 17.5 % for a fully flexible user. For comparison cost differences around 20 % could also result from increasing the electrolyser or PV plant costs by around 55 % which highlights the importance of using high-quality renewable power profiles. To support this an open-source collaborative repository was developed to facilitate the sharing of measured renewable power profiles and provide tools for both time series analysis and green hydrogen techno-economic assessments.

Green hydrogen has recently gained importance as a key element in the transition to a low-carbon energy future sparking a boom in possible production regions. This article aims at situating incipient hydrogen production in the Argentine province of Río Negro within a global production network (GPN). The early configuration of the hydrogen-GPN includes several stakeholders and is contested in many ways. To explore the possible materialization of the hydrogen economy in Argentina this article links GPN literature to the concept of sociotechnical imaginaries. In so doing this study finds three energy imaginaries linked to hydrogen development: First advocates of green hydrogen (GH2) project a sociotechnical imaginary in which GH2 is expected to promote scientific and technological progress. Second proponents of blue hydrogen point to Vaca Muerta and the role of natural gas for energy autonomy. Third opponents of the GH2 project question the underlying growth and export model emphasizing conservation and domestic energy sovereignty. The competition between different capital fractions i.e. green and fossil currently poses the risk of pro-fossil path decisions and lock-in effects. Current power constellations have led to the replacement of green with low-emission resulting in the promotion of multi-colored hydrogen. This is particularly evident in the draft for the new national hydrogen law and the actors involved in defining the national hydrogen strategy. The conceptual combination of actors and their interests their current power relations and the sociotechnical imaginaries they deploy illustrates how Argentina's energy future is already being shaped today.

The updraft rotating bed gasifier (URBG) offers a sustainable solution for waste-to-energy conversion utilizing low-grade lignite and municipal solid waste (MSW) from metropolitan dumping sites. This study investigates the co-gasification of lignite with various MSW components demonstrating a significant enhancement in gasification efficiency due to the synergistic effects arising from their higher hydrogen-to-carbon (H/C) ratios. We find feedstock blending is key to maximizing gasification efficiency from 11% to 52% while reducing SO emissions from 739 mg/kg to 155 mg/kg. Increasing the combustion zone temperature to 1100 K resulted in a peak hydrogen yield which was 19% higher than at 800 K. However steam management is complicated as increasing it improves hydrogen fraction in produced gas but gasification efficiency is compromised. These findingsshowcase the URBG’s potential to address both energy production and waste management challenges guiding fossil-reliant regions toward a more sustainable energy future.

The need to reduce the carbon footprint of conventional energy sources has made green hydrogen a promising solution for the energy transition. The most environmentally friendly way to produce hydrogen is through water-based production using renewable energy. However the availability of fresh water is limited so switching to wastewater instead of fresh water is the key solution to this problem. In response to this issue the present review reports the main findings of the research studies dealing with the feasibility of hydrogen production from wastewater using various technologies including biological electrochemical and advanced oxidation routes. These methods have been studied in a large number of experiments with the aim of investigating and improving the potential of each method. On the other hand the maturity of solar energy technologies has led researchers to focus on the possibility of harnessing this source and combining it with wastewater treatment techniques for the production of green hydrogen. Therefore the present review pays special attention to solar driven hydrogen production from wastewater by highlighting the potential of several technologies for simultaneous water treatment and green hydrogen production from wastewater. Recent results limitations challenges possible improvements and techno-economic assessments reported by several authors as well as future directions of research and industrial implementation in this field are reported.

Water electrolysis using a proton exchange membrane (PEM) holds substantial promise to produce green hydrogen with zero carbon discharge. Although various techniques are available to produce hydrogen gas the water electrolysis process tends to be more cost-effective with greater advantages for energy storage devices. However one of the challenges associated with PEM water electrolysis is the accumulation of gas bubbles which can impair cell performance and result in lower hydrogen output. Achieving an in-depth knowledge of bubble dynamics during electrolysis is essential for optimal cell performance. This review paper discusses bubble behaviors measuring techniques and other aspects of bubble dynamics in PEM water electrolysis. It also examines bubble behavior under different operating conditions as well as the system geometry. The current review paper will further improve the understanding of bubble dynamics in PEM water electrolysis facilitating more competent inexpensive and feasible green hydrogen production.

As the most attractive energy carrier hydrogen production through electro-chemical water splitting (EWS) is promising for resolving the serious environ-mental problems derived from the rapid consumption of fossil fuels globally. Theproton exchange membrane water electrolyzer (PEMWE) is one of the mostpromising EWS technologies and has achieved great advancements. To offer atimely reference for the progress of the PEMWE system the latest advancementsand developments of PEMWE technology are systematically reviewed. The keycomponents including the electrocatalysts PEM and porous transport layer(PTL) as well as bipolar plate (BPP) are first introduced and discussed followedby the membrane electrode assembly and cell design. The highlights are put onthe design of the electrocatalyst and the relationship of each component on theperformance of the PEMWE. Moreover the current challenges and future per-spectives for the development of PEMWE are also discussed. There is a hope thatthis review can provide a timely reference for future directions in PEMWEchallenges and perspectives.

Methane steam reforming is the most widely adopted hydrogen production technology. To address the challenges associated with the large radial thermal resistance and low mass transfer rates inherent in the tubular packed bed reactors during the MSR process this study proposes a structural design optimization that integrates annular metal foam gas channels along the inner wall of the reforming tubes. Utilizing multi-physics simulation methods and taking the conventional tubular reactor as a baseline a comparative analysis was performed on physical parameters that characterize flow behavior heat transfer and reaction in the reforming process. The integration of the annular channels induces a radially non-uniform distribution of flow resistance in the tubes. Since the metal foam exhibits lower resistance the fluid preferentially flows through the annular channels leading to a diversion effect that enhances both convective heat transfer and mass transfer. The diversion effect redirects the central flow toward the near-wall region where the higher reactant concentration promotes the reaction. Additionally the higher thermal conductivity of the metal foam strengthens radial heat transfer further accelerating the reaction. The effects of operating parameters on performance were also investigated. While a higher inlet velocity tends to hinder the reaction in tubes integrated with annular channels it enhances the diversion effect and convective heat transfer. This offsets the adverse impact maintaining high methane conversion with lower pressure drop and thermal resistance than the conventional tubular reactor does.

The effect of the initial state of ZrO2 on properties of Ni/ZrO2 catalysts for hydrogen production in steam reforming of glycerol was investigated. The catalysts were synthesized by impregnating the supports obtained by varying the treatment temperature of ZrO2‧nH2O and introducing Y2O3 as a promoter. All materials were characterized by thermal analysis X-ray diffraction N2 physisorption scanning electron microscopy H2-TPR NH3-TPD and transmission electron microscopy. The mutual influence of NiO and ZrO2 on the genesis of the phase composition pore structure and reducibility was demonstrated. Different catalytic behavior is explained by influence of the initial form of the support on the size morphology of Ni particles and the support thermal stability. The initial activity of Ni/ZrO2is proportional to the monoclinic phase content. The catalysts based on tetragonal ZrO2 displayed the best stability. For the first time the presence of the aldol condensation products in glycerol steam reforming was demonstrated.

The yield of photovoltaic hydrogen production systems is influenced by a number of factors including weather conditions the cleanliness of photovoltaic modules and operational efficiency. Temporal variations in weather conditions have been shown to significantly impact the output of photovoltaic systems thereby influencing hydrogen production. To address the inaccuracies in hydrogen production capacity predictions due to weather-related temporal variations in different regions this study develops a method for predicting photovoltaic hydrogen production capacity using the long short-term memory (LSTM) neural network model. The proposed method integrates meteorological parameters including temperature wind speed precipitation and humidity into a neural network model to estimate the daily solar radiation intensity. This approach is then integrated with a photovoltaic hydrogen production prediction model to estimate the region’s hydrogen production capacity. To validate the accuracy and feasibility of this method meteorological data from Lanzhou China from 2013 to 2022 were used to train the model and test its performance. The results show that the predicted hydrogen production agrees well with the actual values with a low mean absolute percentage error (MAPE) and a high coefficient of determination (R2 ). The predicted hydrogen production in winter has a MAPE of 0.55% and an R2 of 0.985 while the predicted hydrogen production in summer has a slightly higher MAPE of 0.61% and a lower R2 of 0.968 due to higher irradiance levels and weather fluctuations. The present model captures long-term dependencies in the time series data significantly improving prediction accuracy compared to conventional methods. This approach offers a cost-effective and practical solution for predicting photovoltaic hydrogen production demonstrating significant potential for the optimization of the operation of photovoltaic hydrogen production systems in diverse environments.