Production & Supply Chain

This study develops a semi-empirical model of an alkaline water electrolyzer (AWE) based on thermodynamic and electrochemical principles to investigate cell voltage behavior during electrolysis. By importing polarization curve test data under specific operational conditions eight undefined parameters are precisely fitted demonstrating the model’s high accuracy in describing the voltage characteristics of alkaline electrolyzers. Additionally an AWE system model is introduced to examine the influence of various operational parameters on system efficiency. This innovative approach not only provides detailed insights into the operational dynamics of AWE systems but also offers a valuable tool for optimizing performance and enhancing efficiency advancing the understanding and optimization of AWE technologies.

Hydrogen has become a prospective energy carrier for a cleaner more sustainable economy offering carbon-free energy to reduce reliance on fossil fuels and address climate change challenges. However hydrogen production faces significant technological and economic hurdles that must be overcome to reveal its highest potential. This study focused on evaluating the economics and technoeconomic resilience of two large-scale hydrogen production routes from African palm empty fruit bunches (EFB) by indirect gasification. Computer-aided process engineering (CAPE) assessed multiple scenarios to identify bottlenecks and optimize economic performance indicators like gross profits including depreciation after-tax profitability payback period and net present value. Resilience for each route was also assessed considering raw material costs and the market price of hydrogen in relation to gross profits and after-tax profitability. Route 1 achieved a gross profit (DGP) of USD 47.12 million and a profit after taxes (PAT) of USD 28.74 million while Route 2 achieved a DGP of USD 46.53 million and a PAT of USD 28.38 million. The results indicated that Route 2 involving hydrogen production through an indirect gasification reactor with a Selexol solvent unit for carbon dioxide removal demonstrated greater resilience in terms of raw material costs and product selling price.

The production of hydrogen to be used as an alternative renewable energy has been widely explored. Among various methods for producing hydrogen from hydrocarbons methane decomposition is suitable for generating hydrogen with zero greenhouse gas emissions. The use of high temperatures as a result of strong carbon and hydrogen (C–H) bonds may be reduced by utilizing a suitable catalyst with appropriate catalyst support. Catalysts based on transition metals are preferable in terms of their activeness handling and low cost in comparison with noble metals. Further development of catalysts in methane decomposition has been investigated. In this review the recent progress on methane decomposition in terms of catalytic materials preparation method the physicochemical properties of the catalysts and their performance in methane decomposition were presented. The formation of carbon as part of the reaction was also discussed.

This research delineates a pivotal advancement in the domain of sustainable energy systems with a focused emphasis on the integration of renewable energy sources—predominantly wind and solar power—into the hydrogen production paradigm. At the core of this scientific endeavor is the formulation and implementation of a deep-learning-based framework for short-term localized weather forecasting specifically designed to enhance the efficiency of hydrogen production derived from renewable energy sources. The study presents a comprehensive evaluation of the efficacy of fully connected neural networks (FCNs) and convolutional neural networks (CNNs) within the realm of deep learning aimed at refining the accuracy of renewable energy forecasts. These methodologies have demonstrated remarkable proficiency in navigating the inherent complexities and variabilities associated with renewable energy systems thereby significantly improving the reliability and precision of predictions pertaining to energy output. The cornerstone of this investigation is the deployment of an artificial intelligence (AI)-driven weather forecasting system which meticulously analyzes data procured from 25 distinct weather monitoring stations across Latvia. This system is specifically tailored to deliver short-term (1 h ahead) forecasts employing a comprehensive sensor fusion approach to accurately predicting wind and solar power outputs. A major finding of this research is the achievement of a mean squared error (MSE) of 1.36 in the forecasting model underscoring the potential of this approach in optimizing renewable energy utilization for hydrogen production. Furthermore the paper elucidates the construction of the forecasting model revealing that the integration of sensor fusion significantly enhances the model’s predictive capabilities by leveraging data from multiple sources to generate a more accurate and robust forecast. The entire codebase developed during this research endeavor has been made available on an open access GIT server.

Water electrolysis using a proton exchange membrane (PEM) holds substantial promise to produce green hydrogen with zero carbon discharge. Although various techniques are available to produce hydrogen gas the water electrolysis process tends to be more cost-effective with greater advantages for energy storage devices. However one of the challenges associated with PEM water electrolysis is the accumulation of gas bubbles which can impair cell performance and result in lower hydrogen output. Achieving an in-depth knowledge of bubble dynamics during electrolysis is essential for optimal cell performance. This review paper discusses bubble behaviors measuring techniques and other aspects of bubble dynamics in PEM water electrolysis. It also examines bubble behavior under different operating conditions as well as the system geometry. The current review paper will further improve the understanding of bubble dynamics in PEM water electrolysis facilitating more competent inexpensive and feasible green hydrogen production.

When offshore wind farms are connected to a hydrogen plant with dedicated transmission lines for example high-voltage direct current the fluctuation of wind speed will influence the efficiency of the alkaline electrolyzer and deteriorate the techno-economic performance. To overcome this issue firstly an additional heating process is adopted to achieve insulation for the alkaline solution when power generated by wind farms is below the alkaline electrolyzer minimum power threshold while the alkaline electrolyzer overload feature is used to generate hydrogen when wind power is at its peak. Then a simplified piecewise model-based alkaline electrolyzer techno-economic analysis model is proposed. The improved economic performance of the islanded green hydrogen system with the proposed operation strategy is verified based on the wind speed data set simulation generated by the Weibull distribution. Lastly the sensitivity of the total return on investment to wind speed parameters was investigated and an islanded green hydrogen system capacity allocation based on the proposed analysis model was conducted. The simulation result shows the total energy utilization increased from 62.0768% to 72.5419% and the return on investment increased from 5.1303%/month to 5.9581%/month when the proposed control strategy is adopted.

As the commercialisation of two contrasting solar-powered water splitting devices with lower TRLs of proton exchange membrane (PEM) electrolyser systems and photoelectrochemical (PEC) systems gains momentum the path towards a sustainable H2 economy is taking shape. Ongoing pilot projects and demonstration plants are proving the feasibility and potential of these technologies in real-world applications. However to ensure their success we must confront the critical challenges of cost reduction and efficiency enhancement making green H2 economically competitive with traditional production methods. To achieve this a collaborative effort among academia industry and policymakers is paramount. This comprehensive review begins by examining traditional water electrolysis methods focusing on the production of green H2 through electrochemical splitting. It delves into crucial components and advancements in the PEM systems addressing challenges related to catalysts membranes gas diffusion layers and bipolar plates. The review also explores solar-driven PEC water splitting emphasizing the significance of efficient photoelectrodes and reactor design. Additionally it discusses the integration of photovoltaic cells with electrochemical or PEC systems for higher H2 yield. Commercialisation is underway and this endeavour necessitates a collaborative approach with active involvement from academia industry and policymakers. This collective effort not only propels us towards greener and more sustainable energy solutions but also represents a transformative step in the global journey towards a sustainable and environmentally conscious economy.

The International Energy Agency (IEA) established the "H2 Implementing Agreement (HIA)" to promote H2 transition in various economic sectors. Today less than one percent of the world's H2 production is “Green”. Lack of regulations high production costs and inadequate infrastructure are significant impediments. The U.S. Department of Energy set a "111-target" which translates into $1/kg-H2 in the next decade. Many countries in the Middle East and North Africa (MENA) region have announced ambitious plans to produce green H2. Through techno-economic metrics and the impact of economies of scale this study investigates H2@Scale production. H2 Production Analysis and the System Advisor Model developed by the U.S. Department of Energy were used for analysis. The results demonstrate a significant decrease in the levelized cost of H2 (LCOH) when the production volume is scaled up. It was determined that the key cost drivers are capital cost energy installed balance of the plant and mechanical and electrical subsystems. The studied location is found promising for scaled production and developing its commodity status. The findings could serve as a benchmark for key stakeholders investors policymakers and the developer of relevant strategies in the infrastructure and H2 value chain.

Electrolytic hydrogen produced using renewable electricity can help lower carbon dioxide emissions in sectors where feedstocks reducing agents dense fuels or high temperatures are required. This study investigates the implications of various standards being proposed to certify that the grid electricity used is renewable. The standards vary in how strictly they match the renewable generation to the electrolyser demand in time and space. Using an energy system model we compare electricity procurement strategies to meet a constant hydrogen demand for selected European countries in 2025 and 2030. We compare cases where no additional renewable generators are procured with cases where the electrolyser demand is matched to additional supply from local renewable generators on an annual monthly or hourly basis. We show that local additionality is required to guarantee low emissions. For the annually and monthly matched case we demonstrate that baseload operation of the electrolysis leads to using fossil-fuelled generation from the grid for some hours resulting in higher emissions than the case without hydrogen demand. In the hourly matched case hydrogen production does not increase system-level emissions but baseload operation results in high costs for providing constant supply if only wind solar and short-term battery storage are available. Flexible operation or buffering hydrogen with storage either in steel tanks or underground caverns reduces the cost penalty of hourly versus annual matching to 7%–8%. Hydrogen production with monthly matching can reduce system emissions if the electrolysers operate flexibly or the renewable generation share is large. The largest emission reduction is achieved with hourly matching when surplus electricity generation can be sold to the grid. We conclude that flexible operation of the electrolysis should be supported to guarantee low emissions and low hydrogen production costs.

This paper presents a new economic profitability model for a power-to-gas plant producing green hydrogen at the site of an existing wind power plant injected into the gas grid. The model is based on a 42 MW wind power plant for which an optimal electrolyzer of 10 MW was calculated based on the 2500 equivalent full load hours per year and the projection of electricity prices. The model is calculated on an hourly level for all variables of the 25 years of the model. With the calculated breakeven electricity price of 74.23 EUR/MWh and the price of green hydrogen production of 99.44 EUR/MWh in 2045 the wind power plant would produce 22410 MWh of green hydrogen from 31% of its total electricity production. Green hydrogen injected into the gas system would reduce the level of CO2 emissions by 4482 tons. However with the projected prices of natural gas and electricity the wind power plant would cover only 20% of the income generated by the electricity delivered to the grid by producing green hydrogen. By calculating different scenarios in the model the authors concluded that the introduction of a premium subsidy model is necessary to accelerate deployment of electrolyzers at the site of an existing wind power plant in order to increase the wind farm profitability.