This paper addresses the sector-coupling principle, highlights each associated sector’s technologies and showcases their future development, according to the German grid development plan. Furthermore, the research project ESM-Regio, and its goals in terms of simulatively analyzing the sector-coupling approach for a specific model region and future scenarios, is introduced. In this context, the key methods for modeling the electricity sector’s loading behavior are showcased. Most importantly, the state-space load flow calculation, load modeling (including the integration of the power demands of the sector-coupling technologies) and an assessment of grid operating equipment, based on thermal aging models, are described.

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 study presents community-specific modeling approaches for simulating power injection from photovoltaic and wind energy systems in a German metropolitan region. Developed within the EMN_SIM project and based on openly accessible datasets, the methods are broadly transferable across Germany. For PV, a cluster-based model groups systems by geographic and technical characteristics, using real weather data to reduce computational effort. Validation against measured specific yields shows strong agreement, confirming energetic accuracy. The wind model operates on a per-turbine basis, integrating technical specifications, land use, and high-resolution wind data. Energetic validation indicates good consistency with Bavarian reference values, while power-based comparisons with selected turbines show reasonable correlation, subject to expected limitations in wind data resolution. The resulting high-resolution generation profiles reveal spatial and temporal patterns valuable for grid planning and targeted policy design. While further validation with additional measurement data could enhance model precision, the current results already offer a robust foundation for urban energy system analyses and future grid integration studies.

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.