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In which way, and in which sectors, will renewable energy be integrated in the German Energy System by 2030, 2040, and 2050? How can the resulting energy system be characterised following a −95% greenhouse gas emission reduction scenario? Which role will hydrogen play? To address these research questions, techno-economic energy system modelling was performed. Evaluation of the resulting operation of energy technologies was carried out from a system and a business point of view. Special consideration of gas technologies, such as hydrogen production, transport, and storage, was taken as a large-scale and long-term energy storage option and key enabler for the decarbonisation of the non-electric sectors. The broad set of results gives insight into the entangled interactions of the future energy technology portfolio and its operation within a coupled energy system. Amongst other energy demands, CO2 emissions, hydrogen production, and future power plant capacities are presented. One main conclusion is that integrating the first elements of a large-scale hydrogen infrastructure into the German energy system, already, by 2030 is necessary for ensuring the supply of upscaling demands across all sectors. Within the regulatory regime of 2020, it seems that this decision may come too late, which jeopardises the achievement of transition targets within the horizon 2050.

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A variety of models have emerged in the field of energy system analysis to answer a wide range of research questions centred around a sustainable future for the energy sector. Even models designed to address similar issues often have a different focus or modelling approach. Thus, model experiments are a vital tool to provide an overview of the range of models and enable decision-makers to make meaningful model choices. Such comparisons are executed based on a harmonised data set to ensure a high degree of comparability. In the MODEX project cluster, six model experiments, including 40 energy system models, were conducted, and efforts were made to harmonise the input data within the individual comparison and beyond them in the consortium. The experiences and findings of the consortium on how data harmonisation could be performed are presented in this paper. In particular, the focus lies on data transparency to ensure a high degree of reproducibility. A key finding is that while model heterogeneity complicates harmonisation, an early focus on data research and scenario design promotes the creation of a common data set. The metadata collection can provide a significant advantage for the use of model experiment results by external scientists and the data acquisition process itself because of the predefined machine-readable and standardised format.