Jürgen Karl

Hydrogen from biogenic sources is central to the transition to a carbon-neutral energy system, offering flexibility for mobility and industrial applications. Decentralized steam reforming of biogas enables on-site hydrogen production but requires precise heat management due to its strongly endothermic nature. In small-scale systems, conventional manufacturing approaches often limit geometric flexibility and thermal integration, whereas additive manufacturing enables highly integrated reactor structures that overcome these constraints. This study presents the development and experimental evaluation of a compact, monolithic reformer additively manufactured from silicon-infiltrated silicon carbide, combining combustion and reforming zones in a single component to enhance heat transfer and compactness. The reactor features an internal U-shaped reforming channel filled with a nickel-based catalyst and was tested under varying loads. CH₄ conversions of 95–99% close to equilibrium were achieved at gas hourly space velocities up to 75,000 h⁻¹. Stable internal heat supply sustained reforming, although combustion results remain preliminary due to manufacturing-related blockages in the combustion channels, as revealed by computed tomography (CT) analysis. Energy assessments indicate that thermal efficiency is primarily limited by external heat losses of up to 46%, resulting from the high operating temperatures and small reactor dimensions. The results demonstrate the feasibility of the integrated reactor concept while highlighting current limitations related to manufacturability and heat losses, providing a basis for future optimization and scale-up.

This work presents a high-resolution, sector-coupled energy system modeling framework developed within the research project ESM-Regio, designed to analyze regional energy transitions and the sector coupling potential in the context of Germany’s 2045 climate targets. In contrast to existing regional energy system models, our framework explicitly models medium-voltage distribution grids and incorporates asset aging into a sector-coupled techno-economic optimization. The framework operates on the medium-voltage level at a 15-minute temporal resolution and is designed to analyze regions ranging city to county (NUTS-3 level). The electricity, heat, transport, and gas sectors are integrated into the framework using a component-based simulation architecture. All sectors are represented with sectoral submodels which are iteratively coupled through alternating simulation and mixed-integer optimization stages to minimize operational system costs while accounting for technical grid constraints and asset aging. The methodology is applied to the distribution grid area of the regional utility Stadtwerke Bayreuth, for three representative weeks in each of the years 2019, 2030, and 2045. The results highlight the increasing importance of coordinated flexibility—such as building thermal inertia, battery storage, and electric vehicles—in mitigating grid stress under increased electrification. Across the investigated scenarios, coordinated flexibility usage reduces energy procurement costs by up to 22% and significantly lowers line and transformer loading. However, we find that while intelligent flexibility usage can reduce the need for grid expansion, it can not completely eliminate it in the carbon-neutral 2045 scenarios. The presented framework offers a scalable, data-driven approach to assess the impacts of sector coupling and to support infrastructure and regional energy transition planning aligned with national decarbonization goals.

This work presents a high-resolution, sector-coupled energy system modeling framework developed within the research project ESM-Regio, designed to analyze regional energy transitions in the context of Germany’s 2045 climate targets. The framework operates on the medium-voltage level at a 15-minute temporal resolution and is designed to analyze regions ranging city to county (NUTS-3 level). The electricity, heat, transport, and gas sectors are integrated into the framework using a component-based simulation architecture. All sectors are represented with sectoral submodels which are iteratively coupled through alternating simulation and mixed-integer optimization stages to minimize operational system costs while accounting for technical grid constraints and asset aging. The methodology is applied to the distribution grid area of the regional utility Stadtwerke Bayreuth, for three representative weeks in each of the years 2019, 2030, and 2045. The results highlight the increasing importance of coordinated flexibility—such as building thermal inertia, battery storage, and electric vehicles—in mitigating grid stress under increased electrification. However, we find that while intelligent flexibility usage can reduce the need for grid expansion, it can not completely eliminate it in the carbon-neutral 2045 scenarios. The presented framework offers a scalable, data-driven approach to assess the impacts of sector coupling and to support infrastructure and regional energy transition planning aligned with national decarbonization goals.

Methods of computational intelligence show a high potential for short-term price forecasting of the energy market as they offer the possibility to cope with the complexity, multi-parameter dependency, and non-linearity of pricing mechanisms. While there is a large number of publications applying neural networks to the prediction of electricity prices, the analysis of natural gas and carbon prices remains scarce. Identifying a best practice from the literature, this study presents an iterative approach to optimize both the input values and network configuration of neural networks. We apply the approach to the natural gas and carbon market, sequentially testing autoregressive and exogenous explanatory variables as well as different neural network architectures. We subsequently discuss the influence of architectural properties, input parameters, data preparation, and the models’ resilience to singular events. Results show that the selection of appropriate lags of gas and carbon prices to account for autoregressive properties of the respective time series leads to a high degree of forecasting accuracy. Additionally, including ambient temperature data can slightly reduce errors of natural gas price forecasting whereas carbon price predictions benefit from electricity prices as a further explanatory input. The best configurations presented in this contribution achieve a root mean square error (RMSE) of 0.64 EUR/MWh (natural gas prices) corresponding to a normalized RMSE of 0.037 and 0.33 EUR/t_CO2 (carbon prices) corresponding to a normalized RMSE of 0.023.

The methanation process is discussed as one way to chemically store renewable energy in a future energy system. An important criterion for its application is the availability of compact, low-cost reactor concepts with high conversion rates for decentralized use where the renewable energy is produced. Current research focuses on the maximization of the methane yield through improved temperature control of the exothermic reaction, which attempts to avoid both kinetic and thermodynamic limitations. In this context, traditional manufacturing methods limit the design options of the reactor and thus the temperature control possibilities. The use of additive manufacturing methods removes this restriction and creates new freedom in the design process. This paper formulates the requirements for a novel methanation reactor and presents their implementation to a highly innovative reactor concept called ‘ADDmeth’. By using a conical reaction channel expanding from Ø 8 to 32 mm, three twisted, expanding heat pipes (Ø 8 mm in evaporation zone, Ø 12 mm in condenser zone) and a lattice structure for feed gas preheating and mechanical stabilization of the reactor, the design explicitly exploits the advantages of additive manufacturing. The reactor is very compact with a specific mass of 0.36 kg/kW and has a high share of functional volume of 52%. The reactor development was accompanied by tensile tests of additively manufactured samples with the used material 1.4404 (316 L), strength calculations for stability verification and feasibility studies on the printability of fine structures. Ultimate tensile strengths of up to 750 N/mm² (at room temperature) and sufficiently high safety factors of the pressure-loaded structures against yielding were determined. Finally, the paper presents the manufactured bench-scale reactor ADDmeth1 and its implementation.

To achieve the greenhouse gas reduction targets formulated in the European Green Deal, energy- and resource-intensive industries such as the steel industry will have to adapt or convert their production. In the long term, new technologies are promising. However, carbon capture storage and utilization solutions could be considered as short-term retrofitting solutions for existing steelworks. In this context, this paper presents a first experimental demonstration of an approach to the utilization of process off-gases generated in a steelworks by producing methane and methanol in hydrogen-intensified syntheses. Specifically, the integration of two methane synthesis reactors and one methanol synthesis reactor into a steel plant is experimentally simulated. An innovative monitoring and control tool, namely, a dispatch controller, simulates the process off-gas production using a digital twin of the steel plant and optimizes its distribution to existing and new consumers. The operating states/modes of the three reactors resulting from the optimization problem to be solved by the dispatch controller are distributed in real time via an online OPC UA connection to the corresponding experimental plants or their operators and applied there in a decentralized manner. The live coupling test showed that operating values for the different systems can be distributed in parallel from the dispatch controller to the test rigs via the established communication structure without loss. The calculation of a suitable control strategy is performed with a time resolution of one minute, taking into account the three reactors and the relevant steelworks components. Two of each of the methane/methanol synthesis reactors were operated error-free at one time for 10 and 7 h, respectively, with datasets provided by the dispatch controller. All three reactor systems were able to react quickly and stably to dynamic changes in the load or feed gas composition. Consistently high conversions and yields were achieved with low by-product formation.