United Arab Emirates

The concerns regarding the consumption of traditional fuels such as oil and coal have driven the proposals for several cleaner alternatives in recent years. Hydrogen energy is one of the most attractive alternatives for the currently used fossil fuels with several superiorities such as zero-emission and high energy content. Hydrogen has numerous advantages compared to conventional fuels and as such has been employed in gas turbines (GTs) in recent years. The main benefit of using hydrogen in power generation with the GT is the considerably lower emission of greenhouse gases. The performance of the GTs using hydrogen as a fuel is influenced by several factors including the performance of the components the operating condition ambient condition etc. These factors have been investigated by several scholars and scientists in this field. In this article studies on hydrogen-fired GTs are reviewed and their results are discussed. Furthermore some recommendations are proposed for the upcoming works in this field.

Rapid industrialization is consuming too much energy and non-renewable energy resources are currently supplying the world’s majority of energy requirements. As a result the global energy mix is being pushed towards renewable and sustainable energy sources by the world’s future energy plan and climate change. Thus hydrogen has been suggested as a potential energy source for sustainable development. Currently the production of hydrogen from fossil fuels is dominant in the world and its utilization is increasing daily. As discussed in the paper a large amount of hydrogen is used in rocket engines oil refining ammonia production and many other processes. This paper also analyzes the environmental impacts of hydrogen utilization in various applications such as iron and steel production rocket engines ammonia production and hydrogenation. It is predicted that all of our fossil fuels will run out soon if we continue to consume them at our current pace of consumption. Hydrogen is only ecologically friendly when it is produced from renewable energy. Therefore a transition towards hydrogen production from renewable energy resources such as solar geothermal and wind is necessary. However many things need to be achieved before we can transition from a fossil-fuel-driven economy to one based on renewable energy

Hydrogen is a new promising energy source. Three operating parameters including inlet gas flow rate pH and impeller speed mainly determine the biohydrogen production from membrane bioreactor. The work aims to boost biohydrogen production by determining the optimal values of the control parameters. The proposed methodology contains two parts: modeling and parameter estimation. A robust ANIFS model to simulate a membrane bioreactor has been constructed for the modeling stage. Compared with RMS thanks to ANFIS the RMSE decreased from 2.89 using ANOVA to 0.0183 using ANFIS. Capturing the proper correlation between the inputs and output of the membrane bioreactor process system encourages the constructed ANFIS model to predict the output performance exactly. Then the optimal operating parameters were identified using the honey badger algorithm. During the optimization process inlet gas flow rate pH and impeller speed are used as decision variables whereas the biohydrogen production is the objective function required to be maximum. The integration between ANFIS and HBA boosted the hydrogen production yield from 23.8 L to 25.52 L increasing by 7.22%.

Demand for hydrogen has grown and continues to rise as a versatile energy carrier. Hydrogen can be produced from renewable and non-renewable energy sources. A wide range of technologies to produce hydrogen in an environmentally friendly way have been developed. As the life cycle assessment (LCA) approach has become popular recently including in the hydrogen energy system this paper comprehensively reviews the LCA of hydrogen production technology. A subdivision based on the trends in the LCA studies hydrogen production technology goal and scope definition system boundary and environmental performance of hydrogen production is discussed in this review. Thermochemical hydrogen production is the most studied technology in LCA. However utilizing natural resources especially wind power in the electrolysis process stands out as an environmentally preferable solution when compared to alternative production processes. It is crucial to rethink reactors and other production-related equipment to improve environmental performance and increase hydrogen production efficiency. Since most of the previous LCA studies were conducted in developed countries and only a few were from developing countries a way forward for LCA application on hydrogen in developing countries was also highlighted and discussed. This review provides a comprehensive insight for further research on hydrogen production technology from an LCA perspective.

Fuel cell- and electric-powered trucks are promising technologies for zero-emission heavyduty transportation. Recently Fuel Cell Trucks (FCT) have gained wider acceptance as the technology of choice for long-distance trips due to their lighter weight and shorter fueling time than electric-powered trucks. Broader adoption of Fuel Cell Trucks (FCT) requires planning strategies for locating future hydrogen refueling stations (HRS) especially for fleets that transport freight along intercity and inter-country highways. Existing mathematical models of HRS placement often focus on inner-city layouts which make them inadequate when studying the intercity and intercountry FCT operation scale of FCT. Furthermore the same models rarely consider decentralized hydrogen production from renewable energy sources essential for decarbonizing the transportation sector. This paper proposes a mathematical model to guide the planning of the hydrogen infrastructure to support future long-haul FCTs. First the model uses Geographic Information System (GIS) data to determine the HRS’s optimal number and location placement. Then the model categorizes and compares potential hydrogen production sources including off-site delivery and on-site solar-to-hydrogen production. The proposed model is illustrated through a case study of the west coastal area of the United States (from Baja California Mexico to British Columbia Canada). Different geospatial scenarios were tested ranging from the current operational distance of FCEV (250km) and future releases of hydrogen FCT (up to 1500km). Results highlight the capabilities of the model in identifying the number and location of the HRS based on operation distances in addition to determining the optimal hydrogen production technology for each HRS. The findings also confirm the viability of green hydrogen production through solar energy which could play a critical role in a low-carbon transportation future.

Hydrogen and methane as secondary fuels in diesel engines can be promising solutions to meet energy demand. The current study investigated the effect of the specialty gases of different compositions on diesel engine performance and exhaust gases. Four gases with various compositions of exhaust gas recirculation (Carbon monoxide Carbon dioxide and Nitrogen) and fuels (Hydrogen and Methane) were used at various mass flow rates of 10 20 and 25 LPM (liter per minute) and various engine speeds of 2000 2500 3000 and 3500 rpm (revolutions per minute). The procured results revealed that adding specialty gases improved brake thermal efficiency and power. Similarly the brake-specific fuel consumption was also massively retarded compared to diesel due to the influence of the hydrogen and methane composition. However the fuel with the higher nitrogen reported less BTE (brake thermal efficiency) and comparatively higher exhaust gas temperature owing to the higher presence of nitrogen in their composition. Regarding emissions including exhaust gas recirculation dropped the formation of pollutants efficiently compared to diesel. Among various fuels Case 1 (30 % H2 5 % CH4 5 CO2 and 60 % CO) reported the lowest emission of NOx and Case 2 (25 % H2 5 % CH4 5 CO2 30 % CO and 35 % N2) of CO and CO2 emissions. Generally specialty gases with a variable composition of exhaust gas recirculation gases can be a promising sustainable replacement for existing fossil fuels.

The aim of this paper is the design and implementation of an advanced model predictive control (MPC) strategy for the management of a wind–solar microgrid (MG) both in the islanded and grid-connected modes. The MG includes energy storage systems (ESSs) and interacts with external hydrogen and electricity consumers as an extra feature. The system participates in two different electricity markets i.e. the daily and real-time markets characterized by different time-scales. Thus a high-layer control (HLC) and a low-layer control (LLC) are developed for the daily market and the real-time market respectively. The sporadic characteristics of renewable energy sources and the variations in load demand are also briefly discussed by proposing a controller based on the stochastic MPC approach. Numerical simulations with real wind and solar generation profiles and spot prices show that the proposed controller optimally manages the ESSs even when there is a deviation between the predicted scenario determined at the HLC and the real-time one managed by the LLC. Finally the strategy is tested on a lab-scale MG set up at Khalifa University Abu Dhabi UAE.

Advancements in water electrolysis technologies are crucial for green hydrogen production. Proton exchange membrane water electrolysis (PEMWE) is characterized by its efficiency and environmental benefits. The pre diction and optimization of hydrogen production rates (HPRs) in PEMWE systems is difficult and still challenging because of the complexity of the system as well as the operational parameters. The integration of artificial in telligence (AI) and machine learning (ML) appears to be effective in optimization within the energy sector. Hence this work employs the artificial neural network (ANN) to develop a model that accurately predicts HPR in PEMWE setups. A novel approach is introduced by employing the Levenberg–Marquardt backpropagation (LMBP) algorithm for training the ANN. This model is designed to predict HPR based on critical operational parameters including anode and cathode areas (mm2 ) cell voltage (V) and current (A) water flow rate (mL/ min) power (W) and temperature (K). The optimized ANN configuration features an architecture with 7 input nodes two hidden layers of 64 neurons each and a single output node. The performance of the ANN model was evaluated against conventional regression models using key metrics: mean squared error (MSE) coefficient of determination (R2 ) and mean absolute error (MAE). The findings of this study reveal that the developed ANN model significantly outperforms traditional models achieving an R2 value of 0.9989 and an MAE of 0.012. In comparison random forest (R2 = 0.9795) linear regression (R2 = 0.9697) and support vector machines (R2 = − 0.4812) show lower predictive accuracy underscoring the ANN model’s superior performance. This work demonstrates the efficiency of the LMBP in enhancing hydrogen production forecasts and sets a foundation for future improvements in PEMWE efficiency. By enabling precise control and optimization of operational pa rameters this study contributes to the broader goal of advancing green hydrogen production as a viable and scalable alternative to fossil fuels offering both immediate and long-term benefits to sustainable energy initiatives.

The global energy sector accounts for ~75% of total greenhouse gas (GHG) emissions. Low-carbon energy carriers such as hydrogen are seen as necessary to enable an energy transition away from the current fossilderived energy paradigm. Thus the hydrogen economy concept is a key part of decarbonizing the global en ergy system. Hydrogen storage and transport are two of key elements of hydrogen economy. Hydrogen can be stored in various forms including its gaseous liquid and solid states as well as derived chemical molecules. Among these liquid hydrogen due to its high energy density ambient storage pressure high hydrogen purity (no contamination risks) and mature technology (stationary liquid hydrogen storage) is suitable for the transport of large-volumes of hydrogen over long distances and has gained increased attention in recent years. However there are critical obstacles to the development of liquid hydrogen systems namely an energy intensive liquefaction process (~13.8 kWh/kgLH2) and high hydrogen boil-off losses (liquid hydrogen evaporation during storage 1–5% per day). This review focuses on the current state of technology development related to the liquid hydrogen supply chain. Hydrogen liquefaction cryogenic storage technologies liquid hydrogen transmission methods and liquid hydrogen regasification processes are discussed in terms of current industrial applications and underlying technologies to understand the drivers and barriers for liquid hydrogen to become a commer cially viable part of the emerging global hydrogen economy. A key finding of this technical review is that liquid hydrogen can play an important role in the hydrogen economy - as long as necessary technological transport and storage innovations are achieved in parallel to technology demonstrations and market development efforts by countries committed liquid hydrogen as part of their hydrogen strategies.