Saudi Arabia
Underground Hydrogen Storage in Salt Cavern: A Review of Advantages, Challenges, and Prospects
Jun 2025
Publication
The transition to a sustainable energy future hinges on the development of reliable large-scale hydrogen storage solutions to balance the intermittency of renewable energy and decarbonize hard-to-abate industries. Underground hydrogen storage (UHS) in salt caverns emerged as a technically and economically viable strategy leveraging the unique geomechanical properties of salt formations—including low permeability self-healing capabilities and chemical inertness—to ensure safe and high-purity hydrogen storage under cyclic loading conditions. This review provides a comprehensive analysis of the advantages of salt cavern hydrogen storage such as rapid injection and extraction capabilities cost-effectiveness compared to other storage methods (e.g. hydrogen storage in depleted oil and gas reservoirs aquifers and aboveground tanks) and minimal environmental impact. It also addresses critical challenges including hydrogen embrittlement microbial activity and regulatory fragmentation. Through global case studies best operational practices for risk mitigation in real-world applications are highlighted such as adaptive solution mining techniques and microbial monitoring. Focusing on China’s regional potential this study evaluates the hydrogen storage feasibility of stratified salt areas such as Jiangsu Jintan Hubei Yunying and Henan Pingdingshan. By integrating technological innovation policy coordination and cross-sector collaboration salt cavern hydrogen storage is poised to play a pivotal role in realizing a resilient hydrogen economy bridging the gap between renewable energy production and industrial decarbonization.
Flexible Economic Energy Management Including Environmental Indices in Heat and Electrical Microgrids Considering Heat Pump with Renewable and Storage Systems
Oct 2025
Publication
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.
Comparative Techno-economic Optimization of Microgrid Configurations Using Hybrid Battery-hydrogen Storage: NEOM Case Study, Saudi Arabia
Sep 2025
Publication
Renewable energy systems are at the core of global efforts to reduce greenhouse gas (GHG) emissions and to combat climate change. Focusing on the role of energy storage in enhancing dependability and efficiency this paper investigates the design and optimization of a completely sustainable hybrid energy system. Furthermore hybrid storage systems have been used to evaluate their viability and cost-benefits. Examined under a 100% renewable energy microgrid framework three setup configurations are as follows: (1) photovoltaic (PV) and Battery Storage System (BSS) (2) Hybrid PV/Wind Turbine (WT)/BSS and (3) Integrated PV/WT/BSS/Electrolyzer/ Hydrogen Tank/Fuel Cell (FC). Using its geographical solar irradiance and wind speed data this paper inspires on an industrial community in Neom Saudi Arabia. HOMER software evaluates technical and economic aspects net present cost (NPC) levelized cost of energy (COE) and operating costs. The results indicate that the PV/ BSS configuration offers the most sustainable solution with a net present cost (NPC) of $2.42M and a levelized cost of electricity (LCOE) of $0.112/kWh achieving zero emissions. However it has lower reliability as validated by the provided LPSP. In contrast the PV/WT/BSS/Elec/FC system with a higher NPC of $2.30M and LCOE of $0.106/kWh provides improved energy dependability. The PV/WT/BSS system with an NPC of $2.11M and LCOE of $0.0968/kWh offers a slightly lower cost but does not provide the same level of reliability. The surplus energy has been implemented for hydrogen production. A sensitivity analysis was performed to evaluate the impact of uncertainties in renewable resource availability and economic parameters. The results demonstrate significant variability in system performance across different scenarios
Accurate Prediction of Green Hydrogen Production Based on Solid Oxide Electrolysis Cell via Soft Computing Algorithms
Oct 2025
Publication
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.
Low to Near-zero CO2 Production of Hydrogen from Fossil Fuels: Critical Role of Microwave-initiated Catalysis
Apr 2025
Publication
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.
Techno-economic Optimization of Renewable Hydrogen Infrastructure via AI-based Dynamic Pricing
Aug 2025
Publication
This study presents a techno-economic optimization of hydrogen production using hybrid wind-solar systems across six Australian cities highlighting Australia’s green hydrogen potential. A hybrid PVwind-electrolyzer-hydrogen tank (PV-WT-EL-HT) system demonstrated superior performance with Perth achieving the lowest Levelized Cost of Hydrogen (LCOH) at $0.582/kg Net Present Cost (NPC) of $27.5k and Levelized Cost of Electricity (LCOE) of $0.0166/kWh. Perth also showed the highest return on investment present worth and annual worth making it the preferred project site. All locations maintained a 100% renewable fraction proving the viability of fully decarbonized hydrogen production. Metaheuristic validation using nine algorithms showed the Mayfly Algorithm improved techno-economic metrics by 3–8% over HOMER Pro models. The Gray Wolf and Whale Optimization Algorithms enhanced system stability under wind-dominant conditions. Sensitivity analysis revealed that blockchain-based dynamic pricing and reinforcement learning-driven demand response yielded 8–10% cost savings under ±15% demand variability. Nevertheless regional disparities persist; southern cities such as Hobart and Melbourne exhibited 20–30% higher LCOH due to reduced renewable resource availability while densely urbanized cities like Sydney presented optimization ceilings with minimal LCOH improvements despite algorithmic refinements. Investment in advanced materials (e.g. perovskite-VAWTs) and offshore platforms targeting hydrogen export markets is essential. Perth emerged as the optimal hub with hybrid PV/WT/B systems producing 200–250 MWh/ month of electricity and 200–250 kg/month of hydrogen supported by policy incentives. This work offers a blueprint for region-specific AI-augmented hydrogen systems to drive Australia’s hydrogen economy toward $2.10/kg by 2030.
A Comprehensive Review of Green Hydrogen-based Hybrid Energy Systems: Technologies, Evaluation, and Process Safety
Aug 2025
Publication
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.
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