Saudi Arabia

Presently there is no single clear route for the near-term production of the huge volumes of CO2-free hydrogen necessary for the global transition to any type of hydrogen economy. All conventional routes to produce hydrogen from hydrocarbon fossil fuels (notably natural gas) involve the production—and hence the emission—of CO2 most notably in the steam methane reforming (SMR) process. Our recent studies have highlighted another route; namely the critical role played by the microwave-initiated catalytic pyrolysis decomposition or deconstruction of fossil hydrocarbon fuels to produce hydrogen with low to near-zero CO2 emissions together with high-value solid nanoscale carbonaceous materials. These innovations have been applied firstly to wax then methane crude oil diesel then biomass and most recently Saudi Arabian light crude oil as well as plastics waste. Microwave catalysis has therefore now emerged as a highly effective route for the rapid and effective production of hydrogen and high-value carbon nanomaterials co-products in many cases accompanied by low to near-zero CO2 emissions. Underpinning all of these advances has been the important concept from solid state physics of the so-called Size-Induced-Metal-Insulator Transition (SIMIT) in mesoscale or mesoscopic particles of catalysts. The mesoscale refers to a range of physical scale in-between the micro- and the macro-scale of matter (Huang W Li J and Edwards PP 2018 Mesoscience: exploring the common principle at mesoscale Natl. Sci. Rev. 5 321-326 (doi:10.1093/nsr/nwx083)). We highlight here that the actual physical size of the mesoscopic catalyst particles located close to the SIMIT is the primary cause of their enhanced microwave absorption and rapid heating of particles to initiate the catalytic—and highly selective—breaking of carbon–hydrogen bonds in fossil hydrocarbons and plastics to produce clean hydrogen and nanoscale carbonaceous materials. Importantly also since the surrounding ‘bath’ of hydrocarbons is cooler than the microwave-heated catalytic particles themselves the produced neutral hydrogen molecule can quickly diffuse from the active sites. This important feature of microwave heating thereby minimizes undesirable side reactions a common feature of conventional thermal heating in heterogeneous catalysis. The low to near-zero CO2 production of hydrogen via microwave-initiated decomposition or cracking of abundant hydrocarbon fossil fuels may be an interim viable alternative to the conventional widely-used SMR that a highly efficient process but unfortunately associated with the emission of vast quantities of CO2. Microwave-initiated catalytic decomposition also opens up the intriguing possibility of using distributed methane in the current natural gas structure to produce hydrogen and high-value solid carbon at either central or distributed sites. That approach will lessen many of the safety and environmental concerns associated with transporting hydrogen using the existing natural gas infrastructure. When completely optimized microwave-initiated catalytic decomposition of methane (and indeed all hydrocarbon sources) will produce no aerial carbon (CO2) and only solid carbon as a co-product. Furthermore reaction conditions can surely be optimized to target the production of high-quality synthetic graphite as the major carbon-product; that material of considerable importance as the anode material for lithium-ion batteries. Even without aiming for such products derived from the solid carbon co-product it is of course far easier to capture solid carbon rather than capturing gaseous CO2 at either the central or distributed sites. Through microwave-initiated catalytic pyrolysis this decarbonization of fossil fuels can now become the potent source of sustainable hydrogen and high-value carbon nanomaterials.

The reliability and sustainability of multi-energy networks are increasingly critical in addressing modern energy demands and environmental concerns. Hydrogen-based hybrid energy systems can mitigate the challenges of renewable energy utilization such as intermittency grid stability and energy storage by integrating hydrogen generation and electricity storage from renewable sources such as solar and wind. Therefore this review offers a comprehensive evaluation of the environmental economic and technological aspects of green hydrogen-based hybrid energy systems particularly highlighting improvements in terms of the economics of fuel cell and electrolysis procedures. It also highlights new approaches such as hybrid energy management strategies and power-to-gas (PtG) conversion to enhance the system’s dependability and resilience. Analyzing the role of green hydrogen-based hybrid energy systems in supporting global climate goals and improving energy security underscores their high potential to make a significant contribution to carbon-neutral energy networks and provide policymakers with useful recommendations for developing guidelines. In addition the social aspect of hydrogen systems like energy equity and community engagement towards a hydrogen-based society provides reasons for the continued development of next-generation energy systems.

The solid oxide electrolysis cell (SOEC) presents significant potential for transforming renewable energy into green hydrogen. Traditional modeling approaches however are constrained by their applicability to specific SOEC systems. This study aims to develop robust data-driven models that accurately capture the complex relationships between input and output parameters within the hydrogen production process. To achieve this advanced machine learning techniques were utilized including Random Forests (RFs) Convolutional Neural Networks (CNNs) Linear Regression Artificial Neural Networks (ANNs) Elastic Net Ridge and Lasso Regressions Decision Trees (DTs) Support Vector Machines (SVMs) k-Nearest Neighbors (KNN) Gradient Boosting Machines (GBMs) Extreme Gradient Boosting (XGBoost) Light Gradient Boosting Machines (LightGBM) CatBoost and Gaussian Process. These models were trained and validated using a dataset consisting of 351 data points with performance evaluated through various metrics and visual methods. The dataset’s suitability for model training was confirmed using the Monte Carlo outlier detection method. Results indicate that within the dataset and evaluation framework of this study ANNs CNNs Gradient Boosting and XGBoost models have demonstrated high accuracy and reliability achieving the largest R-squared scores and the smallest error metrics. Sensitivity analysis reveals that all input parameters significantly influence hydrogen production magnitude. Game-theoretic SHAP values underline current and cathode electrode conditions as critical factors. This research determines the performance of machine learning models particularly ANNs CNNs Gradient Boosting and XGBoost in predicting hydrogen production through the SOEC process. The outcomes of this paper can provide a certain reference for related research and applications in the hydrogen production field.

Developing new injection systems and combustion chambers for hydrogen is a central topic for the new generation of engines. In this effort simulations take a central role but methods developed for conventional hydrocarbons (methane kerosene) must be revisited for hydrogen. Validation then becomes an essential part and clean well documented experiments are needed to guaranty that computational fluid dynamics solvers are as predictive and accurate as expected. In this framework the HYLON case is a swirled hydrogen/air burner used by multiple groups worldwide to validate simulation methods for hydrogen combustion in configurations close to gas turbine burners with experimental data available through the TNF web site. The present study compares recent Raman spectroscopy and Particle Image Velocimetry measurements and Large Eddy Simulations (LES). The LES results are evaluated against a dataset comprising mean and RMS measurements of H2 N2 O2 H2O molar fractions temperature and velocity fields offering new insights into flame stabilization mechanisms. The simulations incorporate conjugate heat transfer to predict the combustor wall temperatures and are conducted for two atmospheric-pressure operating conditions each representing distinct combustion regimes diffusion and partially premixed. Novelty and significance statement Data on confined hydrogen flames in burner similar as industrial ones are limited. This work aims to fill this gap by performing multiple and simultaneous diagnostics on the swirled hydrogen-air flame called HYLON. For the first time in such a swirled configuration mean and RMS fields of temperature main species and velocities are compared to LES allowing new insight into the potential and limits of the models as well as the physics of these flames. These experimental results will be made available on TNF as over 30 research groups worldwide have expressed interest in using them.

This study discusses energy management in thermal and electrical microgrids while taking heat pumps renewable sources thermal and hydrogen storages into account. The weighted total of the operating cost grid emissions level voltage and temperature deviation function and other factors makes up the objective function of the suggested method. The restrictions include the operationflexibility model of resources and storages micro-grid flexibility limits and optimum power flow equations. Point Estimation Method is used in this work to simulate load energy price and renewable phenomenon uncertainty. A fuzzy decision-making methodology is used to arrive at a compromise solution that satisfies network operators’ operational environmental and financial goals. The innovations of this paper include energy management of various smart microgrids simultaneous modeling of several indicators especially flexibility investigation of optimal performance of resources and storage devices and modeling of uncertainty considering low computational time and an accurate flexibility model. Numerical findings indicate that the fuzzy decision-making approach has the capability to reach a compromise point in which the objective functions approach their minimum values. The integration of the proposed uncertainty modeling with precise flexibility modeling results in a reduction in computational time when compared to stochastic optimization based on scenarios. For the compromise point and uncertainty modeling with PEM by efficiently managing resources and thermal and hydrogen storages scheme is capable of attaining high flexibility conditions. Compared to load flow studies the approach can enhance the operational environmental and economic conditions of smart microgrids by approximately 33–57% 68% and 33–68% respectively under these circumstances.

This study investigates numerically combustion attributes and NOx formation of premixed ammonia-hydrogen/air flames within a swirl burner of a gas turbine considering various conditions of hydrogen fraction (HF: 0 % 5 % 30 % 40 % and 50 %) equivalence ratio (φ: 0.85 1.0 and 1.2) and mixture inlet temperature (Tin: 400–600 K). The results illustrate that flame temperature increases with hydrogen addition from 1958 K for pure ammonia to 2253 K at 50 % HF. Raising the inlet temperature from 400 K to 600 K markedly enhances combustion intensity resulting in an increase of the Damköhler number (Da) from 117 to 287. NOx levels rise from ∼1800 ppm (0 % HF) to ∼7500 ppm (50 % HF) and peak at 8243 ppm under lean conditions (φ = 0.85). Individual NO N2O and NO2 emissions also reach maxima at φ = 0.85 with values of 5870 ppm 2364 ppm and 10 ppm respectively decreasing significantly under richer conditions (2547 ppm 1245 ppm and 5 ppm at φ = 1.2). These results contribute to advancing low-carbon fuel technologies and highlight the viability of ammonia-hydrogen co-firing as a pathway toward sustainable gas turbine operation.

The rock wettability is one of the most critical parameters that influences rock storage potential trapping and H2 withdrawal rate during Underground hydrogen storage (UHS). However the existing review articles on wettability of H2-brine-rock systems do not provide detailed information on complexities introduced by reservoir wettability influencing parameters such as high pressure temperature salinity conditions micro-biotic effects cushion gases and organic acids relevant to subsurface environments. Therefore a comprehensive review of existing research on various parameters influencing rock wettability during UHS and residual trapping of H2 was conducted in this study. Literature that provides insight into molecular-level interaction through machine learning and molecular dynamic (MD) simulations and role of surface-active chemicals such as nanoparticles surfactants and wastewater chemicals were also reviewed. The review suggested that UHS could be feasible in clean geo-storage formations but the presence of rock surface contaminants at higher storage depth and microbial effects should be accounted for to prevent over-estimation of the rock storage potentials. The H2 wettability of storage/caprocks and associated risks of UHS projects could be higher in rocks with high proportion of carbonate minerals organic-rich shale and basalt with high plagioclase minerals content. However treatment of rock surfaces with nanofluids surfactants methylene blue and methyl orange has proven to alter the rock wettability from H2-wet towards water-wet. Research results on effect of rock wettability on residually trapped hydrogen and snap-off effects during UHS are contradictory thus further studies would be required in this area. The review generally concludes that rock wettability plays prominent role on H2 storage due to the frequency and cyclic loading of UHS hence it is vital to evaluate the effects of all possible wettability influencing parameters for successful designs and implementation of UHS projects.

Blue hydrogen technology generated from natural gas through carbon capture and storage (CCS) technology is a promising solution to mitigate greenhouse gas emissions and meet the growing demand for clean energy. To improve the sustainability of blue hydrogen it is crucial to explore alternative feedstocks production methods and improve the efficiency and economics of carbon capture storage and utilization strategies. Two established technologies for hydrogen synthesis are Steam Methane Reforming (SMR) and Autothermal Reforming (ATR). The choice between SMR and ATR depends on project specifics including the infrastructure energy availability environmental goals and economic considerations. ATR-based facilities typically generate hydrogen at a lower cost than SMR-based facilities except in cases where electricity prices are elevated or the facility has reduced capacity. Both SMR and ATR are methods used for hydrogen production from methane but ATR offers an advantage in minimizing CO2 emissions per unit of hydrogen generated due to its enhanced energy efficiency and unique process characteristics. ATR provides enhanced utility and flexibility regarding energy sources due to its autothermal characteristics potentially facilitating integration with renewable energy sources. However SMR is easier to run but may lack flexibility compared to ATR necessitating meticulous management. Capital expenditures for SMR and ATR hydrogen reactors are similar at the lower end of the capacity spectrum but when plant capacity exceeds this threshold the capital costs of SMR-based hydrogen production surpass those of ATR-based facilities. The less profitably scaled-up SMR relative to the ATR reactor contributes to the cost disparity. Additionally individual train capacity constraints for SMR CO2 removal units and PSA units increase the expenses of the SMR-based hydrogen facility significantly.