Germany

Hydrogen produced by renewable energy sources (green hydrogen) is at the centrepiece of European decarbonization strategies necessitating large imports from third countries. Egypt potentially stands out as major production hub. While technical and economic viability are broadly discussed in literature analyses of local acceptance are absent. This study closes this gap by surveying 505 locals in the Suez Canal Economic Zone (Port Said and Suez) regarding their attitudes towards renewable energy development and green hydrogen production. We find overall support for both national deployment and export to Europe. Respondents see a key benefit in rising income thereby strongly underlying the economic argument. Improved trade relationships or improved political relationships are seen as potential benefits of export but as less relevant for engaging in cooperation putting a spotlight on local benefits. Our study suggests that the local population is more positive than negative towards the development and scaling up of green hydrogen projects in Egypt.

This study introduces a hybrid energy storage system that combines advanced flywheel technology with hydrogen fuel cells and electrolyzers to address the variability inherent in renewable energy sources like solar and wind. Flywheels provide quick energy dispatch to meet peak demand while hydrogen fuel cells offer sustained power over extended periods. The research explores the strategic integration of these technologies within a hybrid photovoltaic (PV)-flywheel‑hydrogen framework aiming to stabilize the power supply. To evaluate the impact of flywheel integration on system sizing and load fluctuations simulations were conducted both before and after the flywheel integration. The inclusion of the flywheel resulted in a more balanced energy production and consumption profile across different seasons notably reducing the required fuel cell capacity from 100 kW to 30 kW. Additionally the integration significantly enhanced system stability enabling the fuel cell and electrolyzer to operate at consistent power during load fluctuations. The system achieved efficiencies of 71.42 % for the PEM electrolyzer and 62.14 % for the PEM fuel cell. However the introduction of the flywheel requires a higher capacity of PV modules and a larger electrolyzer. The overall flywheel's efficiency was impacted by parasitic energy losses resulting in an overall efficiency of 46.41 %. The minimum efficiency observed across various scenarios of the model studied was 3.14 % highlighting the importance of considering these losses in the overall system design. Despite these challenges the hybrid model demonstrated a substantial improvement in the reliability and stability of renewable energy systems effectively bridging short-term and long-term energy storage solutions.

Hydrogen is a versatile energy carrier which can be produced from variety of feedstocks stored and transported in various forms for multi-functional end-uses in transportation energy and manufacturing sectors. Several regional national and supra-national climate policy frameworks emphasize the need value and importance of Fuel cell and Hydrogen (FCH) technologies for deep and sector-wide decarbonization. Despite these multi-faceted advantages familiar and proven FCH technologies such as alkaline electrolysis and proton-exchange membrane fuel cell (PEMFC) often face economic technical and societal barriers to mass-market adoption. There is no single unified standardized and globally harmonized normative definition of costs. Nevertheless the discussion and debates surrounding plausible candidates and/or constituents integral for assessing the economics and value proposition of status-quo as well as developmental FCH technologies are steadily increasing—Life Cycle Costing (LCC) being one of them if not the most important outcome of such exercises.<br/>To that end this review article seeks to improve our collective understanding of LCC of FCH technologies by scrutinizing close to a few hundred publications drawn from representative databases—SCOPUS and Web of Science encompassing several tens of technologies for production and select transportation storage and end-user utilization cases. This comprehensive review forms part of and serves as the basis for the Clean Hydrogen Partnership funded SH2E project whose ultimate goal is the methodical development a formal set of principles and guardrails for evaluating the economic environmental and social impacts of FCH technologies. Additionally the SH2E projects will also facilitate the proper comparison of different FCH technologies whilst reconciling range of technologies methodologies modelling assumptions and parameterization found in existing literature.

Assessing the sustainable development of green hydrogen and assessing its potential environmental impacts using the Life Cycle Assessment is crucial. Challenges in LCA like missing environmental data are often addressed using machine learning such as artificial neural networks. However to find an ML solution researchers need to read extensive literature or consult experts. This research demonstrates how customised LLMs trained with domain-specific papers can help researchers overcome these challenges. By starting small by consolidating papers focused on the LCA of proton exchange membrane water electrolysis which produces green hydrogen and ML applications in LCA. These papers are uploaded to OpenAI to create the LlamaIndex enabling future queries. Using the LangChain framework researchers query the customised model (GPT-3.5-turbo) receiving tailored responses. The results demonstrate that customised LLMs can assist researchers in providing suitable ML solutions to address data inaccuracies and gaps. The ability to quickly query an LLM and receive an integrated response across relevant sources presents an improvement over manually retrieving and reading individual papers. This shows that leveraging fine-tuned LLMs can empower researchers to conduct LCAs more efficiently and effectively.

Hydrogen refueling stations (HRS) can cause a significant fraction of the hydrogen refueling cost. The main cost contributor is the currently used mechanical compressor. Electrochemical hydrogen compression (EHC) has recently been proposed as an alternative. However its optimal integration in an HRS has yet to be investigated. In this study we compare the performance of a gaseous HRS equipped with different compressors. First we develop dynamic models of three process configurations which differ in the compressor technology: mechanical vs. electrochemical vs. combined. Then the design and operation of the compressors are optimized by solving multi-stage dynamic optimization problems. The optimization results show that the three configurations lead to comparable hydrogen dispensing costs because the electrochemical configuration exhibits lower capital cost but higher energy demand and thus operating cost than the mechanical configuration. The combined configuration is a trade-off with intermediate capital and operating cost.

The derivation of an efficient operational strategy for storing intermittent renewable energies using a hybrid battery-hydrogen energy storage system is a difficult task. One approach for deriving an efficient operational strategy is using mathematical optimization in the context of model predictive control. However mathematical optimization derives an operational strategy based on a non-exact mathematical system representation for a specified prediction horizon to optimize a specified target. Thus the resulting operational strategies can vary depending on the optimization settings. This work focuses on evaluating potential improvements in the operational strategy for a hybrid batteryhydrogen energy storage system using mathematical optimization. To investigate the operation a simulation model of a hybrid energy storage system and a tailor-made mixed integer linear programming optimization model of this specific system are utilized in the context of a model predictive control framework. The resulting operational strategies for different settings of the model predictive control framework are compared to a rule-based controller to show the potential benefits of model predictive control compared to a conventional approach. Furthermore an in-depth analysis of different factors that impact the effectiveness of the model predictive controller is done. Therefore a sensitivity analysis of the effect of different electricity demands and resource sizes on the performance relative to a rule-based controller is conducted. The model predictive controller reduced the energy consumption by at least 3.9 % and up to 17.9% compared to a rule-based controller. Finally Pareto fronts for multi-objective optimizations with different prediction and control horizons are derived and compared to the results of a rule-based controller. A cost reduction of up to 47 % is achieved by a model predictive controller with a prediction horizon of 7 days and perfect foresight. Keywords: Model Predictive Control Optimization Mixed Integer Linear Programming Hybrid Battery-Hydrogen Energy Storage System

While hydrogen is regularly discussed as a possible option for storing regenerative energies its low minimum ignition energy and broad range of explosive concentrations pose safety challenges regarding hydrogen storage and there are also challenges related to hydrogen production and transport and at the point of use. A risk assessment of the whole hydrogen energy system is necessary to develop hydrogen utilization further. Here we concentrate on the most important hydrogen storage technologies especially high-pressure storage liquid hydrogen in cryogenic tanks methanol storage and salt cavern storage. This review aims to study the most recent research results related to these storage techniques by describing typical sensors and explosion protection measures thus allowing for a risk assessment of hydrogen storage through these technologies.

To meet the new regulation for the deployment of alternative fuels infrastructure which sets targets for electric recharging and hydrogen refuelling infrastructure by 2025 or 2030 a large infrastructure comprising trucksuitable hydrogen refuelling stations will soon be required. However further standardisation is required to support the uptake of hydrogen for heavy-duty transport for Europe’s green energy future. Hydrogen-powered vehicles require pure hydrogen as some contaminants can reduce the performance of the fuel cell even at very low levels. Even if previous projects have paved the way for the development of the European quality infrastructure for hydrogen conformity assessment sampling systems and methods have yet to be developed for heavy-duty hydrogen refuelling stations (HD-HRS). This study reviews different aspects of the sampling of hydrogen at heavy-duty hydrogen refuelling stations for purity assessment with a focus on the current and future specifications and operations at HD-HRS. This study describes the state-of-the art of sampling systems currently under development for use at HD-HRS and highlights a number of aspects which must be taken into consideration to ensure safe and accurate sampling: risk assessment for the whole sampling exercise selection of cylinders methods to prepare cylinders before the sampling filling pressure and venting of the sampling systems.

Hydrogen-driven heavy-duty trucks are a promising technology for reducing CO2 emissions in the transportation sector. Thus storing hydrogen efficiently onboard is vital. The three available or currently developed physical hydrogen storage technologies (compressed gaseous subcooled liquid and cryo-compressed hydrogen) are promising solutions. For a profound thermodynamic comparison of these storage systems a universally applicable model is required. Thus this article introduces a generalized thermodynamic model and conducts thermodynamic comparisons in terms of typical drive cycle scenarios. Therefore a model introduced by Hamacher et al. [1] for cryo-compressed hydrogen tanks is generalized by means of an explicit model formulation using the property ��2� from REFPROP [2] which is understood as a generic specific isochoric two-phase heat capacity. Due to an implemented decision logic minor changes to the equation system are automatically made whenever the operation mode or phase of the tank changes. The resulting model can simulate all three storage tank systems in all operating scenarios and conditions in the single- and two-phase region. Additionally the explicit model formulation provides deeper insights into the thermodynamic processes in the tank. The model is applied to the three physical hydrogen storage technologies to compare drive cycles heat requirement dormancy behavior and optimal usable density. The highest driving ranges were achieved with cryo-compressed hydrogen however it also comes with higher heating requirements compared to subcooled liquid hydrogen.