Egypt

This work reports on H2 fuel generation from sewage water using Cu/CuO nanoporous (NP) electrodes. This is a novel concept for converting contaminated water into H2 fuel. The preparation of Cu/CuO NP was achieved using a simple thermal combustion process of Cu metallic foil at 550 ◦C for 1 h. The Cu/CuO surface consists of island-like structures with an inter-distance of 100 nm. Each island has a highly porous surface with a pore diameter of about 250 nm. X-ray diffraction (XRD) confirmed the formation of monoclinic Cu/CuO NP material with a crystallite size of 89 nm. The prepared Cu/CuO photoelectrode was applied for H2 generation from sewage water achieving an incident to photon conversion efficiency (IPCE) of 14.6%. Further the effects of light intensity and wavelength on the photoelectrode performance were assessed. The current density (Jph) value increased from 2.17 to 4.7 mA·cm−2 upon raising the light power density from 50 to 100 mW·cm−2 . Moreover the enthalpy (∆H*) and entropy (∆S*) values of Cu/CuO electrode were determined as 9.519 KJ mol−1 and 180.4 JK−1 ·mol−1 respectively. The results obtained in the present study are very promising for solving the problem of energy in far regions by converting sewage water to H2 fuel.

Africa is rich with an abundance of renewable energy sources that can help meeting the continent’s demand for electricity to promote economic growth and meet global targets for CO2 reduction. Green Hydrogen is considered one of the most promising technologies for energy generation transportation and storage. In this paper the prospects of green hydrogen production potential in Africa are investigated along with its usage for future implementation. Moreover an overview of the benefits of shifting to green Hydrogen technology is presented. The current African infrastructure and policies are tested against future targets and goals. Furthermore the study embraces a detailed theoretical environmental technological and economic assessment putting the local energy demands into consideration.

The world is facing a challenge in meeting its needs for energy. Global energy consumption in the last half-century has increased very rapidly and is expected to continue to grow over the next 50 years. However it is expected to see significant differences between the last 50 years and the next. This paper aims at introducing a good solution to replace or work with conventional marine power plants. This includes the use of fuel cell power plant operated with hydrogen produced through water electrolysis or hydrogen produced from natural gas gasoline or diesel fuels through steam reforming processes to mitigate air pollution from ships.

DFT calculations at B3LYP/6-31g(dp) with the D3 version of Grimme’s dispersion are performed to investigate the application of TM-encapsulated Mg12O12 nano-cages (TM= Mn Fe and Co) as a hydrogen storage material. The molecular dynamic (MD) calculations are utilized to examine the stability of the considered structures. TD-DFT method reveals that the TM-encapsulation converts the Mg12O12 from an ultraviolet into a visible optical active material. The adsorption energy values indicate that the Mn and Fe atoms encapsulation enhances the adsorption of H2 molecules on the Mg12O12 nano-cage. The pristine Mg12O12 and CoMg12O12 do not meet the requirements for hydrogen storage materials while the MnMg12O12 and FeMg12O12 obey the requirements. MnMg12O12 and FeMg12O12 can carry up to twelve and nine H2 molecules respectively. The hydrogen adsorption causes a redshift for the λmax value of the UV-Vis. spectra of the MnMg12O12 and FeMg12O12 nano-cages. The thermodynamic calculations show that the hydrogen storage reaction for MnMg12O12 nano-cage is a spontaneous reaction while for FeMg12O12 nano-cage is not spontaneous. The results suggested that the MnMg12O12 nano-cage may be a promising material for hydrogen storage applications.

The use of hybrid renewable energy systems (HRES) has become the best option for supplying electricity to sites remote from the central power system because of its sustainability environmental friendliness and its low cost of energy compared to many conventional sources such as diesel generators. Due to the intermittent nature of renewable energy resources there is a need however for an energy storage system (ESS) to store the surplus energy and feed the energy deficit. Most renewable sources used battery storage systems (BSS) a green hydrogen storage system (GHSS) and a diesel generator as a backup for these sources. Batteries are very expensive and have a very short lifetime and GHSS have a very expensive initial cost and many security issues. In this paper a system consisting of wind turbines and a photovoltaic (PV) array with a pumped hydro energy storage (PHES) system as the main energy storage to replace the expensive and short lifetime batteries is proposed. The proposed system is built to feed a remote area called Dumah Aljandal in the north of Saudi Arabia. A smart grid is used via a novel demand response strategy (DRS) with a dynamic tariff to reduce the size of the components and it reduces the cost of energy compared to a flat tariff. The use of the PHES with smart DRS reduced the cost of energy by 34.2% and 41.1% compared to the use of BSS and GHSS as an ESS respectively. Moreover the use of 100% green energy sources will avoid the emission of an estimated 2.5 million tons of greenhouse gases every year. The proposed system will use a novel optimization algorithm called the gradually reduced particles of particle swarm optimization (GRP-PSO) algorithm to enhance the exploration and exploitation during the searching iterations. The GRP-PSO reduces the convergence time to 58% compared to the average convergence time of 10 optimization algorithms used for comparison. A sensitivity analysis study is introduced in this paper in which the effect of ±20% change in wind speed and solar irradiance are selected and the system showed a low effect of these resources on the Levelized cost of energy of the HRES. These outstanding results proved the superiority of using a pumped-storage system with a dynamic tariff demand response strategy compared to the other energy storage systems with flat-rate tariffs.

In this paper a new isolated hybrid system is simulated and analyzed to obtain the optimal sizing and meet the electricity demand with cost improvement for servicing a small remote area with a peak load of 420 kW. The major configuration of this hybrid system is Photovoltaic (PV) modules Biomass gasifier (BG) Electrolyzer units Hydrogen Tank units (HT) and Fuel Cell (FC) system. A recent optimization algorithm namely Mayfly Optimization Algorithm (MOA) is utilized to ensure that all load demand is met at the lowest energy cost (EC) and minimize the greenhouse gas (GHG) emissions of the proposed system. The MOA is selected as it collects the main merits of swarm intelligence and evolutionary algorithms; hence it has good convergence characteristics. To ensure the superiority of the selected MOA the obtained results are compared with other well-known optimization algorithms namely Sooty Tern Optimization Algorithm (STOA) Whale Optimization Algorithm (WOA) and Sine Cosine Algorithm (SCA). The results reveal that the suggested MOA achieves the best system design achieving a stable convergence characteristic after 44 iterations. MOA yielded the best EC with 0.2106533 $/kWh the net present cost (NPC) with 6170134 $ the loss of power supply probability (LPSP) with 0.05993% and GHG with 792.534 t/y.

Decarbonization of the steel industry is one of the pathways towards a fossil-fuel-free environment. The steel industry is one of the top contributors to greenhouse gas emissions. Most of these emissions are directly linked to the use of a fossil-fuelbased reductant. Replacing the fossil-based reductant with green H2 enables the transition towards a fossil-free steel industry. The carbon-free iron produced will cause the refining and steelmaking operations to have a starting point far from today’s operations. In addition to carbon being an alloying element in steel production carbon addition controls the melting characteristics of the reduced iron. In the present study the effect of carbon content and form (cementite/graphite) in hydrogen-reduced iron ore pellets on their melting characteristics was examined by means of a differential thermal analyser and optical dilatometer. Carburized samples with a carbon content < 2 wt % did not show any initial melting at the eutectic temperature. At and above 2 wt % the carburized samples showed an initial melting at the eutectic temperature irrespective of the carbon content. However the absorbed heat varies with varied carbon content. The carbon form does not affect the initial melting temperature but it affects the melting progression. Carburized samples melt homogenously while melting of iron-graphite mixtures occurs locally at the interface between iron and carbon particles and when the time is not long enough melting might not occur to any significant extent. Therefore at any given carbon content > 2 wt % the molten fraction is higher in the case of carburized samples which is indicated by the amount of absorbed melting heat.

Dihydrogen (H2) commonly named ‘hydrogen’ is increasingly recognised as a clean and reliable energy vector for decarbonisation and defossilisation by various sectors. The global hydrogen demand is projected to increase from 70 million tonnes in 2019 to 120 million tonnes by 2024. Hydrogen development should also meet the seventh goal of ‘affordable and clean energy’ of the United Nations. Here we review hydrogen production and life cycle analysis hydrogen geological storage and hydrogen utilisation. Hydrogen is produced by water electrolysis steam methane reforming methane pyrolysis and coal gasification. We compare the environmental impact of hydrogen production routes by life cycle analysis. Hydrogen is used in power systems transportation hydrocarbon and ammonia production and metallugical industries. Overall combining electrolysis-generated hydrogen with hydrogen storage in underground porous media such as geological reservoirs and salt caverns is well suited for shifting excess of-peak energy to meet dispatchable on-peak demand.

The Energy Management Strategy (EMS) in Fuel Cell Hybrid Electric Vehicles (FCHEVs) is the key part to enhance optimal power distribution. Indeed the most recent works are focusing on optimizing hydrogen consumption without taking into consideration the degradation of embedded energy sources. In order to overcome this lack of knowledge this paper describes a new health-conscious EMS algorithm based on Model Predictive Control (MPC) which aims to minimize the battery degradation to extend its lifetime. In this proposed algorithm the health-conscious EMS is normalized in order to address its multi-objective optimization. Then weighting factors are assigned in the objective function to minimize the selected criteria. Compared to most EMSs based on optimization techniques this proposed approach does not require any information about the speed profile which allows it to be used for real-time control of FCHEV. The achieved simulation results show that the proposed approach reduces the economic cost up to 50% for some speed profile keeping the battery pack in a safe range and significantly reducing energy sources degradation. The proposed health-conscious EMS has been validated experimentally and its online operation ability clearly highlighted on a PEMFC delivery postal vehicle.