Hydrogen-based Renewable Energy Research Articles

Technical and Economic Feasibility Study of a Hybrid Hydrogen-based Renewable Energy System

Traditional electrical grids rely heavily on Hydrocarbons. The latter turn out to be a significant cause of environmental damage, as well as being rapidly depleted. Remote regions and settlements cannot benefit from this kind of electric energy as they are disconnected from the electrical network. Hybrid renewable energy systems (HRES) proved as being a great option in such cases. The objective of this article is to construct and optimize an autonomous hybrid renewable power plant to meet the demand for electricity for an isolated drilling location in Adrar region in the south of Algeria. To address the issue of intermittent power from wind and solar sources, a hydrogen-based arrangement is included in the already existing hybrid renewable energy system. The system modeling and running are carried out using HOMER package to identify the best cost-effective HRES arrangements.

Ultra-low metal loading rhodium phosphide electrode for efficient alkaline hydrogen evolution reaction

The practical production of hydrogen from water electrolyzers demands efficient electrocatalysts with maximized and optimized active sites that promote the Hydrogen Evolution Reaction (HER) at wide pH ranges. Herein, we successfully synthesized a rhodium-based nanomaterial with extremely low metal loading (2 μg/cm−2) as electrocatalyst for the HER. In particular, the material consists of carbon-supported rhodium phosphide (Rh2P) as active sites, which are partially covered with carbon patches. The so-developed nanomaterial exhibits high crystallinity, resistance to sintering, and outstanding electrocatalytic activity and operational stability in an extended pH interval. Notably, Rh2P displays specific-mass activities, ca. 2.5- and 5-fold higher than those of the benchmark 20 wt% Pt/C at an overpotential of 50 mV in acidic and alkaline media, respectively. Comparison of the electrocatalytic performance of the current Rh2P electrocatalyst with those of phosphorus-free rhodium NPs and an alternative rhodium phosphide nanomaterial, reveals that the inclusion of phosphorus atoms, the purity and crystallinity of the Rh2P phase are critical to boost the electrocatalytic HER. This is corroborated by theoretical simulations using DFT, which also prove that the presence of C-patches on Rh2P favors the H2O dissociation during HER electrocatalytic cycle and prevents phosphorous leaching. Overall, this work provides new insights for the rational design and controlled synthesis of small NPs for using as efficient electrocatalysts in hydrogen-based renewable energy devices.

Maximizing Green Hydrogen Production from Water Electrocatalysis: Modeling and Optimization

The use of green hydrogen as a fuel source for marine applications has the potential to significantly reduce the carbon footprint of the industry. The development of a sustainable and cost-effective method for producing green hydrogen has gained a lot of attention. Water electrolysis is the best and most environmentally friendly method for producing green hydrogen-based renewable energy. Therefore, identifying the ideal operating parameters of the water electrolysis process is critical to hydrogen production. Three controlling factors must be appropriately identified to boost hydrogen generation, namely electrolysis time (min), electric voltage (V), and catalyst amount (μg). The proposed methodology contains the following two phases: modeling and optimization. Initially, a robust model of the water electrolysis process in terms of controlling factors was established using an adaptive neuro-fuzzy inference system (ANFIS) based on the experimental dataset. After that, a modern pelican optimization algorithm (POA) was employed to identify the ideal parameters of electrolysis duration, electric voltage, and catalyst amount to enhance hydrogen production. Compared to the measured datasets and response surface methodology (RSM), the integration of ANFIS and POA improved the generated hydrogen by around 1.3% and 1.7%, respectively. Overall, this study highlights the potential of ANFIS modeling and optimal parameter identification in optimizing the performance of solar-powered water electrocatalysis systems for green hydrogen production in marine applications. This research could pave the way for the more widespread adoption of this technology in the marine industry, which would help to reduce the industry’s carbon footprint and promote sustainability.

Novel Ni–Cr-based alloys as hydrogen fuel sources through alkaline water electrolytes

The hydrogen evolution reaction (HER) from water splitting is particularly attractive for green and clean power sources, but it remains a significant challenging issue. For the successful application of hydrogen-based renewable energy such as fuel cells, highly active and cost-saving metallic electro-catalysts for H2 fuel production are vital. The goal of this study is to look into the effects of alloyed molybdenum, chromium, and iron on the electrocatalytic activity of Ni-based alloys in an alkaline electrolyte for HER. SEM with an energy dispersive spectroscopy (EDX) unit was used to determine the chemical composition of alloys. The electrocatalytic effectiveness of the explored cathodes on HER was evaluated in alkaline solutions employing open circuit potential measurements, linear polarization and electrochemical impedance spectroscopy (EIS). The impact of KOH concentrations on HER rate was also investigated. Tafel curves were used to calculate the HER's kinetic parameters, and the mechanisms of the HER were discovered. EIS observations at HER's cathodic potential have been explored and compared to a theoretical model. The Ni–Cr–Mo–Fe alloy has a low over-potential of 232 mV @ 10 mA cm−2 and a Tafel slope of 57.7 mV dec−1 in 1.0 M KOH media, resulting in an efficient HER. These findings indicate that the addition of Mo and Fe to Ni–Cr improves the catalytic efficiency of HER significantly. The Ni–Cr–Mo–Fe cathode is an economical and practical material for alkaline HER production.

Robust design optimization and stochastic performance analysis of a grid-connected photovoltaic system with battery storage and hydrogen storage

Balancing of intermittent energy such as solar energy can be achieved by batteries and hydrogen-based storage. However, combining these systems received limited attention in a grid-connected framework and its design optimization is often performed assuming fixed parameters. Hence, such optimization induces designs highly sensitive to real-world uncertainties, resulting in a drastic mismatch between simulated and actual performances. To fill the research gap on design optimization of grid-connected, hydrogen-based renewable energy systems, we performed a computationally efficient robust design optimization under different scenarios and compared the stochastic performance based on the corresponding cumulative density functions. This paper provides the optimized stochastic designs and the advantage of each design based on the financial flexibility of the system owner. The results illustrate that the economically preferred solution is a photovoltaic array when the self-sufficiency ratio is irrelevant (≤30%). When a higher self-sufficiency ratio threshold is of interest, i.e. up to 59%, photovoltaic-battery designs and photovoltaic-battery-hydrogen designs provide the cost-competitive alternatives which are least-sensitive to real-world uncertainty. Conclusively, including storage systems improves the probability of attaining an affordable levelized cost of electricity over the system lifetime. Future work will focus on the integration of the heat demand.

Risk-constrained probabilistic optimal scheduling of FCPP-CHP based energy hub considering demand-side resources

Renewable energy sources (RES) with sharing a large percentage of future energy generation capacities play an essential role in the decarbonization of the future electricity and thermal networks as well as transportation sectors. However, the uncertainties in their outputs make some difficulties in making operational decisions. Hydrogen energy plays a considerable role in this concept. Besides, energy hubs (EHs) provide an efficient and reliable framework for gathering multi-type energy carriers.This paper optimally schedules the operating of the EH and decreases the emission cost, considering the electrical and thermal demand response (DR) program in a probabilistic environment. Besides plug-in electric vehicles (PEVs) and a complete model of hydrogen-based renewable energy sources are presented in the EH. Taking into account uncertainties of electrical/thermal energy markets real-time prices, customers' energy demand, and energy production of RESs into account, various scenarios are generated using the Monte Carlo simulation technique. Next, an efficient method is used to reduce the number of the scenario to make the optimization problem computable and fast. In order to reduce the risk of encountering high operating costs, the conditional value at risk (CVaR) technique is used to manage the associated risk. Simulation results show the efficiency of the proposed method in decreasing the operational cost and managing the risk of encountering unfavorable states.

Economic viability assessment of sustainable hydrogen production, storage, and utilisation technologies integrated into on- and off-grid micro-grids: A performance comparison of different meta-heuristics

In recent years, there has been considerable interest in the development of zero-emissions, sustainable energy systems utilising the potential of hydrogen energy technologies. However, the improper long-term economic assessment of costs and consequences of such hydrogen-based renewable energy systems has hindered the transition to the so-called hydrogen economy in many cases. One of the main reasons for this is the inefficiency of the optimization techniques employed to estimate the whole-life costs of such systems. Owing to the highly nonlinear and non-convex nature of the life-cycle cost optimization problems of sustainable energy systems using hydrogen as an energy carrier, meta-heuristic optimization techniques must be utilised to solve them. To this end, using a specifically developed artificial intelligence-based micro-grid capacity planning method, this paper examines the performances of twenty meta-heuristics in solving the optimal design problems of three conceptualised hydrogen-based micro-grids, as test-case systems. Accordingly, the obtained numeric simulation results using MATLAB indicate that some of the newly introduced meta-heuristics can play a key role in facilitating the successful, cost-effective development and implementation of hydrogen supply chain models. Notably, the moth-flame optimization algorithm is found capable of reducing the life-cycle costs of micro-grids by up to 6.5% as compared to the dragonfly algorithm.

The effect of CO2 emissions and economic performance on hydrogen-based renewable production in 35 European Countries

This study applies the OLS and panel data approach to estimate the influence of variables such as greenhouse gas emissions, per capita income, the scale of labor force input, the portion of added value in manufacturing industry and government mechanism on hydrogen-based renewable production in 35 European countries. The empirical results show that the nation's economic input and its income level have a positive effect on hydrogen-based renewable energy, which indicated that the economic growth has promoted living standards, inspired environmental awareness, and influenced the use of alternative energy and renewable energy. Moreover, the empirical results also show that deepening democracy (government mechanism) has a positive impact on hydrogen-based renewable energy in OECD countries, but the impact on non-OECD countries is not clear.

How does hydrogen-based renewable energy change with economic development? Empirical evidence from 32 countries

The hydrogen-based renewable energy resource base is sufficient to meet several times the present world energy demand. This paper analyzes the drivers promoting hydrogen-based renewable energy utilization, focusing on a group of 32 countries by applying panel data techniques. The pooled ordinary least square estimator and fixed effect estimator are employed for comparison. Grey relational analysis is used to explore the relationships at a national level between renewable energy development and its influencing factors. The main results over our time span indicate that: (1) GDP per capita is a significantly positive contributor to renewable energy consumption, while oil price does not present a strong relationship in the use of renewables; (2) social awareness about climate change and concerns for energy security is not enough to motivate the switch from traditional to renewable energy sources; (3) the role of urbanization in renewable energy consumption relies on different stages of the urbanization process, resulting in opposite trends in renewable energy development between developing and developed countries. The results show that the market mechanism is not entirely responsible for encouraging the use of renewables and the role of climate change and energy security concerns in renewables use should be enhanced. By analyzing the results, policy implications are provided for the sustainable development of renewable energy.

04/01961 Ten years of operational experience with a hydrogen-based renewable energy supply system: Ghosh, P. C. et al. Solar Energy, 2003, 75, (6), 469–478

04/01961 Ten years of operational experience with a hydrogen-based renewable energy supply system: Ghosh, P. C. et al. Solar Energy, 2003, 75, (6), 469–478

Ten years of operational experience with a hydrogen-based renewable energy supply system

The PHOEBUS demonstration plant supplied energy to part of the Central Library in Forschungszentrum Jülich, Germany, for 10 years. The technical feasibility of a self-sufficient energy supply system based on photovoltaic, battery and hydrogen storage was demonstrated. The overall efficiency based on the annual energy balance excluding the photovoltaic efficiency varied from 51% to 64%. The battery bank was able to supply energy to the load for three days in the absence of solar radiation. Around 50–52% of the demands were delivered by the battery. In addition, another 20–25% of the demand was supplied by the fuel cell, which indicates that the energy should be stored in a long-term storage system. Thus, the highest level of energetic reliability can be achieved with relatively low battery capacity and hydrogen storage.