Germany

In case of accidental conditions involving high-speed hydrogen combustion the considerable pressure and thermal loads could result in substantial deformation and/or destruction of the industrial appliances. Accounting of such effects in the safety analysis with CFD tools can provide critical information on the design and construction of the sensitive appliances’ elements. The current paper presents the development and the implementation of a new 3D-technique which makes possible to perform simulations of the gas-dynamic processes simultaneously with adaptation of the geometry of complex configurations. Using the data obtained in the experiments on the flame acceleration and DDT in the tubes of industrial arrangements performed in MPA and KIT the authors performed a series of the combustion simulations corresponding to the experimental conditions. The combustion gas-dynamics was simulated using COM3D code and the tube wall material behavior was modelled using finite-element code ABAQUS - © Dassault Systèmes with real-time data exchange between the codes. Obtained numerical results demonstrated good agreement with the observed experimental data on both pressure dynamics and tube deformation history.

Hydrogen production based on a combination of intermittent renewables and grid electricity is a promising approach for reducing emissions in hard-to-decarbonise sectors at lower costs. However for such a configuration to provide climate benefits it is crucial to ensure that the grid electricity consumed in the process is derived from low-carbon sources. This paper examined the use of hourly grid emission factors (EFs) to more accurately determine the short-term climate impact of dynamically operated electrolysers. A model of the interconnected northern European electricity system was developed and used to calculate average grid-mix and marginal EFs for the four bidding zones in Sweden. Operating a 10 MW electrolyser using a combination of onshore wind and grid electricity was found to decrease the levelised cost of hydrogen (LCOH) to 2.40–3.63 €/kgH2 compared with 4.68 €/kgH2 for wind-only operation. A trade-off between LCOH and short-term climate impact was revealed as specific marginal emissions could exceed 20 kgCO2eq/kgH2 at minimum LCOH. Both an emission-minimising operating strategy and an increased wind-to-electrolyser ratio was found to manage this trade-off by enabling simultaneous cost and emission reductions lowering the marginal carbon abatement cost (CAC) from 276.8 €/tCO2eq for wind-only operation to a minimum of 222.7 and 119.3 €/tCO2eq respectively. Both EF and LCOH variations were also identified between the bidding zones but with no notable impact on the marginal CAC. When using average grid-mix emission factors the climate impact was low and the CAC could be reduced to 71.3–200.0 €/tCO2eq. In relation to proposed EU policy it was demonstrated that abiding by hourly renewable temporal matching principles could ensure low marginal emissions at current levels of fossil fuels in the electricity mix.

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.

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.

Converting renewable electricity via water electrolysis into green hydrogen and hydrogen-based products will shape a global trade in power-to-x (PtX) products. The European Union's renewable hydrogen import target of 10 million tonnes by 2030 reflects the urgent need for PtX imports by sea to early high-demand countries like Germany. This study evaluates the cost efficiency and greenhouse gas (GHG) emissions of four hydrogen carrier ship import options considering a reconversion to H2 at the import terminal for a final delivery to offtakers via a H2 pipeline network in 2030. This includes ammonia a liquid organic hydrogen carrier (LOHC) system based on benzyltoluene (BT) and a novel CO2/e-methane and CO2/e-methanol cycle where CO2 is captured at the reconversion plant and then shipped back to the PtX production site in a nearly closed carbon loop. The GHG emission accounting includes well-to-wake emissions of the marine fuels and direct emissions of the carbon capture plant. Two GW-scale case studies reveal the impact of a short and long-distance route from Tunisia and Australia to Germany whereas the specific PtX carriers are either fuelled by its PtX cargo as a renewable marine fuel or by conventional heavy fuel oil (HFO). Ammonia outperforms the other PtX routes as the total hydrogen supply cost range between 5.07 and 7.69 for Australia (low: NH3 HFO high: LOHC HFO) and 4.78–6.21 € per kg H2 for Tunisia (low: NH3 HFO high: CH4 HFO) respectively. The ammonia routes achieve thereby GHG intensities of 31 % and 86 % below the EU threshold of 3.4 kg CO2(e) per kg H2 for renewable hydrogen. LOHC though unless switching to low-emission fuels and the CO2/e-methanol cycle exceed the GHG threshold at shipping distances of 12300 and 16600 km. The hydrogen supply efficiencies vary between 57.9 and 78.8 %LHV (low: CH4 PtX-fuelled high: NH3 HFO) with a PtX marine fuel consumption of up to 15 % LHV for the Australian methanol route whereas high uncertainties remain for the ammonia and methanol reconversion plant efficiencies. The CO2 cyle enables a cost-efficient CO2 supply easing the near-term shortage of climate-neutral CO2 sources at the cost of high GHG emissions for long-distance routes.

Alkaline water electrolysis is a key technology for large-scale hydrogen production. In this process safety and efficiency are among the most essential requirements. Hence optimization strategies must consider both aspects. While experimental optimization studies are the most accurate solution model-based approaches are more cost and time-efficient. However validated process models are needed which consider all important influences and effects of complete alkaline water electrolysis systems. This study presents a dynamic process model for a pressurized alkaline water electrolyzer consisting of four submodels to describe the system behavior regarding gas contamination electrolyte concentration cell potential and temperature. Experimental data from a lab-scale alkaline water electrolysis system was used to validate the model which could then be used to analyze and optimize pressurized alkaline water electrolysis. While steady-state and dynamic solutions were analyzed for typical operating conditions to determine the influence of the process variables a dynamic optimization study was carried out to optimize an electrolyte flow mode switching pattern. Moreover the simulation results could help to understand the impact of each process variable and to develop intelligent concepts for process optimization

A key building block of the European Green Deal is the development of a hydrogen commodity market which requires a suitable hydrogen market design and the timely introduction of related policy measures. Using exploratory interviews with five expert groups we contribute to this novel research field by outlining the core market design criteria and proposing suitable regulations for the future European hydrogen market. We identify detailed recommendations along three core market design focus areas: Market development policy measures infrastructure regulations as well as hydrogen and certificate trading. Our findings provide an across-industry view of current policy-related key challenges in the hydrogen commodity market development and mitigation approaches. We therefore support policymakers within the EU in the ongoing detailing of their regulatory hydrogen and green energy packages. Further we promote hydrogen market development by assisting current and future industry players in finding a common understanding of the future hydrogen market design.

In a future energy generation market the storage of energy is going to become increasingly important. Besides classic ways of storage like pumped storage hydro power stations etc the production of hydrogen will play an important role as an energy storage system. Hydrogen may be stored as a liquefied gas (LH2) on a long term base as well as for short term supply of fuel stations to ensure a so called “green” mobility. The handling with LH2 has been subject to several recent safety studies. In this context reliable simulation tools are necessary to predict the spill and spreading of LH2 during an accidental release. This paper deals with the different boiling regimes: film boiling transition boiling and nucleation boiling after a release and their modeling by means of an inhouse-code for wall evaporation which is implemented in the commercial CFD code ANSYS CFX. The paper will describe the model its implementation and validation against experimental data such as the HSL LH2 spill experiments.

This paper aims to provide a holistic analysis of the role of hydrogen for achieving greenhouse gas neutrality in Germany. For that purpose we apply an integrated energy system model which includes all demand sectors of the German energy system and optimizes the transformation pathway from today's energy system to a future cost-optimal energy system. We show that 412 TWh of hydrogen are needed in the year 2045 mostly in the industry and transport sector. Particularly the use of about 267 TWh of hydrogen in industry is essential as there are no cost-effective alternatives for the required emission reduction in the chemical industry or in steel production. Furthermore we illustrate that the German hydrogen supply in the year 2045 requires both an expansion of domestic electrolyzer capacity to 71 GWH2 and hydrogen imports from other European countries and Northern Africa of about 196 TWh. Moreover flexible operation of electrolyzers is cost-optimal and crucial for balancing the intermittent nature of volatile renewable energy sources. Additionally a conducted sensitivity analysis shows that full domestic hydrogen supply in Germany is possible but requires an electrolyzer capacity of 111 GWH2.

There are a large number of applications in which hydrogen internal combustion engines represent a sensible alternative to battery electric propulsion systems and to fuel cell electric propulsion systems. The main advantages of combustion engines are their high degree of robustness and low manufacturing costs. No critical raw materials are required for production and there are highly developed production plants worldwide. A CO2-free operation is possible when using hydrogen as a fuel. The formation of nitrogen oxides during hydrogen combustion in the engine can be effectively mitigated by a lean-burn combustion process. However achieving low NOx raw emissions conflicts with achieving high power yields. In this work a series industrial diesel engine was converted for hydrogen operation and comprehensive engine tests were carried out. Various measures to improve the trade-off between NOx emissions and performance were investigated and evaluated. The rated power output and the maximum torque of the series diesel engine could be exceeded while maintaining an indicated specific NOx emission of 1 g/kWh along the entire full load curve. In the low-end-torque range however the gap to the full load curve of the series diesel engine could not be fully closed with the hardware used.