Germany

The popularity of climate neutral new energy vehicles for reduced emissions and improved air quality has been raising great attention for many years. World-wide a strong commitment continues to drive the demand for zero-emission through alternative energy sources and propulsion systems. Despite the fact that 71.27% of hydrogen is produced from natural gas green hydrogen is a promising clean way to contribute to and maintain a climate neutral ecosystem. Thereby reaching CO2 targets for 2030 and beyond requires cross-sectoral changes. However the strong motivation of governments for climate neutrality is challenging many sectors. One of them is the transport sector as it is challenged to find viable all-in solutions that satisfy social economic and sustainable requirements. Currently the use of new energy vehicles operating on green sustainable hydrogen technologies such as batteries or fuel cells has been the focus for reducing the mobility induced emissions. In Europe 50% of the total emissions result from mobility. The following article reviews the background ongoing challenges and potentials of new energy vehicles towards the development of an environmentally friendly hydrogen economy. A change management process mindset has been adapted to discuss the key scientific and commercial challenges for a successful transition.

The Life Cycle Sustainability Assessment (LCSA) is a proven method for sustainability assessment. However the interpretation phase of an LCSA is challenging because many different single results are obtained. Additionally performing a Multi-Criteria Decision Analysis (MCDA) is one way—not only for LCSA—to gain clarity about how to interpret the results. One common form of MCDAs are outranking methods. For these type of methods it becomes of utmost importance to clarify when results become preferable. Thus thresholds are commonly used to prevent decisions based on results that are actually indifferent between the analyzed options. In this paper a new approach is presented to identify and quantify such thresholds for Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) based on uncertainty of Life Cycle Impact Assessment (LCIA) methods. Common thresholds and this new approach are discussed using a case study on finding a preferred location for sustainable industrial hydrogen production comparing three locations in European countries. The single LCSA results indicated different preferences for the environmental economic and social assessment. The application of PROMETHEE helped to find a clear solution. The comparison of the newly-specified thresholds based on LCIA uncertainty with default thresholds provided important insights of how to interpret the LCSA results regarding industrial hydrogen production.

Hydrogen-based energy storage has the potential to compensate for the volatility of renewable power generation in energy systems with a high renewable penetration. The operation of these storage facilities can be optimized using automated energy management systems. This work presents a Reinforcement Learning-based energy management approach in the context of CO2-neutral hydrogen production and storage for an industrial combined heat and power application. The economic performance of the presented approach is compared to a rule-based energy management strategy as a lower benchmark and a Dynamic Programming-based unit commitment as an upper benchmark. The comparative analysis highlights both the potential benefits and drawbacks of the implemented Reinforcement Learning approach. The simulation results indicate a promising potential of Reinforcement Learning-based algorithms for hydrogen production planning outperforming the lower benchmark. Furthermore a novel approach in the scientific literature demonstrates that including energy and price forecasts in the Reinforcement Learning observation space significantly improves optimization results and allows the algorithm to take variable prices into account. An unresolved challenge however is balancing multiple conflicting objectives in a setting with few degrees of freedom. As a result no parameterization of the reward function could be found that fully satisfied all predefined targets highlighting one of the major challenges for Reinforcement Learning -based energy management algorithms to overcome.

Proton exchange membrane water electrolysis (PEMWE) is a key technology for future sustainable energy systems. Proton exchange membrane (PEM) electrolysis cells use iridium one of the scarcest elements on earth as catalyst for the oxygen evolution reaction. In the present study the expected iridium demand and potential bottlenecks in the realization of PEMWE for hydrogen production in the targeted GW a−1 scale are assessed in a model built on three pillars: (i) an in-depth analysis of iridium reserves and mine production (ii) technical prospects for the optimization of PEM water electrolyzers and (iii) PEMWE installation rates for a market ramp-up and maturation model covering 50 years. As a main result two necessary preconditions have been identified to meet the immense future iridium demand: first the dramatic reduction of iridium catalyst loading in PEM electrolysis cells and second the development of a recycling infrastructure for iridium catalysts with technical end-of-life recycling rates of at least 90%.

Energy system integration enables raising operational synergies by coupling the energy infrastructures for electricity methane and hydrogen. However this coupling reinforces the infrastructure interdependencies increasing the need for integrated modeling of these infrastructures. To analyze the cost-efficient sustainable and secure dispatch of applied large-scale energy infrastructures an extensive and non-linear optimization problem needs to be solved. This paper introduces a nested decomposition approach with three stages. The method enables an integrated and full-year consideration of large-scale multi-energy systems in hourly resolution taking into account physical laws of power flows in electricity and gas transmission systems as boundary conditions. For this purpose a zooming technique successively reduces the temporal scope while first increasing the spatial and last the technical resolution. A use case proves the applicability of the presented approach to large-scale energy systems. To this end the model is applied to an integrated European energy system model with a detailed focus on Germany in a challenging transport situation. The use case demonstrates the temporal regional and cross-sectoral interdependencies in the dispatch of integrated energy infrastructures and thus the benefits of the introduced approach.

Achieving net-zero emissions by 2050 will require accelerated efforts that include decarbonizing long-haul truck transportation. In this difficult-to-decarbonize low-margin industry economic transparency on technology options is vital for decision makers seeking to eliminate emissions. Battery electric (BET) and hydrogen fuel cell electric trucks (FCET) can represent emission-free alternatives to diesel-powered trucks (DT). Previous studies focus on cost competitiveness in weight-constrained transportation even though logistics research shows that significant shares of transportation are constrained by volume and analyze cost only for selected technologies hence impeding a differentiated market segmentation of future emission-free trucks. In this study the perspective of a rational investor is taken and it is shown that under current conditions in the U.S. BETs outperform FCETs in various long-haul use cases despite charging times and cargo deficits and will further increase their technological competitiveness to DTs. While future energy and fueling prices are decisive for BET competitiveness the analysis reveals that autonomous driving may change the picture in favor of FCETs.

To solve the challenge of decarbonizing the transport sector a broad variety of alternative fuels based on different concepts including Power-to-Gas and Power-to-Liquid and propulsion systems have been developed. The current research landscape is investigating either a selection of fuel options or a selection of criteria a comprehensive overview is missing so far. This study aims to close this gap by providing a holistic analysis of existing fuel and drivetrain options spanning production to utilization. For this purpose a case study for Germany is performed considering different vehicle classes in road rail inland waterway and air transport. The evaluated criteria on the production side include technical maturity costs as well as environmental impacts whereas on the utilization side possible blending with existing fossil fuels and the satisfaction of the required mission ranges are evaluated. Overall the fuels and propulsion systems Methanol-to-Gasoline Fischer–Tropsch diesel and kerosene hydrogen battery-electric propulsion HVO DME and natural gas are identified as promising future options. All of these promising fuels could reach near-zero greenhouse gas emissions bounded to some mandatory preconditions. However the current research landscape is characterized by high insecurity with regard to fuel costs depending on the predicted range and length of value chains.

Over the past two years requirements to meet climate targets have been intensified. In addition to the tightening of the climate targets and the demand for net-zero achievement by as early as 2045 there have been discussions on implementing and realizing these goals. Hydrogen has emerged as a promising climate-neutral energy carrier. Thus over the last 1.5 years more than 25 countries have published hydrogen roadmaps. Furthermore various studies by different authorities have been released to support the development of a hydrogen economy. This paper examines published studies and hydrogen country roadmaps as part of a meta-analysis. Furthermore a market analysis of electrolyzer manufacturers is conducted. The prospected demand for green hydrogen from various studies is compared to electrolyzer manufacturing capacities and selected green hydrogen projects to identify potential market ramp-up scenarios and to evaluate if green hydrogen demand forecasts can be filled.

As a major part of the energy turn around the European Union and other countries are supporting the development of renewable energy technologies to decrease nuclear and fossil energy production. Therefore efficient use of renewable energy resources is one challenge as they are influenced by environmental conditions and hence the intensity of resources such as wind or solar power fluctuates. To secure constant energy supply suitable energy storage and conversion techniques are required. An upcoming solution is the utilization and storage of hydrogen or hydrogen-rich natural gas in porous formations in the underground. In the past microbial methanation was observed as a side effect during these gas storage operations. The concept of underground bio-methanation arised which uses the microbial metabolism to convert hydrogen and carbon dioxide into methane. The concept consists of injecting gaseous hydrogen and carbon dioxide into an underground structure during energy production peaks which are subsequently partly converted into methane. The resulting methane-rich gas mixture is withdrawn during high energy demand. The concept is comparable to engineered bio-reactors which are already locally integrated into the gas infrastructure. In both technologies the conversion process of hydrogen into methane is driven by hydrogenotrophic methanogenic archaea present in the aqueous phase of the natural underground or above-ground engineered reactor. Nevertheless the porous medium in the underground provides compared to the engineered bio-reactors a larger interface between the gas and aqueous phase caused by the enormous volume in the underground porous media. The following article summarizes the potential and concept of underground methanation and the current state of the art in terms of laboratory investigations and pilot tests. A short system potential analysis shows that an underground bio-reactor with a storage capacity of 850 Mio. Sm3 could deliver methane to more than 600000 households based on a hydrogen production from renewable energies.

With the rising threat of climate change green hydrogen is increasingly seen as the high-capacity energy storage and transport medium of the future. This creates an opportunity for low- and middle-income countries to leverage their high renewable energy potential to produce use and export low-cost green hydrogen creating environmental and economic development benefits. While identifying ideal locations for green hydrogen production is critical for countries when defining their green hydrogen strategies there has been a paucity of adequate geospatial planning approaches suitable to low- and middle-income countries. It is essential for these countries to identify green hydrogen production sites which match demand to expected use cases such that their strategies are economically sustainable. This paper therefore develops a novel geospatial cost modelling method to optimize the location of green hydrogen production across different use cases with a focus on suitability to low- and middle-income countries. This method is applied in Kenya to investigate the potential hydrogen supply chain for three use cases: ammonia-based fertilizer freight transport and export. We find hydrogen production costs of e3.7–9.9/kgH2 are currently achievable across Kenya depending on the production location chosen. The cheapest production locations are identified to the south and south-east of Lake Turkana. We show that ammonia produced in Kenya can be cost-competitive given the current energy crisis and that Kenya could export hydrogen to Rotterdam with costs of e7/kgH2 undercutting current market prices regardless of the carrier medium. With expected techno-economic improvements hydrogen production costs across Kenya could drop to e1.8–3.0/kgH2 by 2030.