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An increasing number of municipalities are striving for energy autonomy. This study determines in which municipalities and at what additional cost energy autonomy is feasible for a case study of Germany. An existing municipal energy system optimization model is extended to include the industrial, commercial and personal transport sectors. Multiple regression methods are benchmarked in order to identify the model best suited for the transfer of individual optimization results to a large proportion of German municipalities. The resulting levelized cost of energy (LCOE) from the optimization of representative case study municipalities are transferred using energy-relevant indicators. The study demonstrates that energy autonomy is technically feasible in 6,314 (56%) municipalities. Thereby, the LCOEs increase in the autonomous case on average by 0.41 €/kWh compared to the minimum cost scenario. Apart from energy demand, base-load-capable bioenergy and deep geothermal energy have the greatest influence on the LCOEs. Overall, it appears that municipal energy autonomy is not economically viable under current framework conditions. This study represents a starting point for defining possible scenarios in studies of future national energy system or transmission grid expansion planning, which for the first time consider completely energy autonomous municipalities. [ABSTRACT FROM AUTHOR]

Increasing energy autonomy is one of the main reasons for municipalities to invest in renewable energy technologies. In this study, the potential of weather-robust autonomous energy systems is evaluated for 11 003 German municipalities in over one million parallelized techno-economic optimizations utilizing high-performance computing clusters. For this purpose, a holistic municipal-level energy system model (ETHOS.FineRegions) was developed that minimizes annualized system costs in 2045. The completely energy autonomous supply can be established in around 90% of German municipalities corresponding to 50% of the country's population. Especially highly populated municipalities often do not have the capacity to meet their own energy demands due to low wind and open-field PV potentials. Large rooftop PV capacities account for 40% of installed capacity in the autonomous municipalities. Seasonal storage needs are met by large underground thermal storage tanks and batteries provide intraday storage. Furthermore, huge capacity increases are often required for the final 20% of energy demand to be met in order to achieve a degree of autonomy of 100%. The large storage and rooftop PV capacities lead to high specific system costs in the autonomous municipalities with between 144 €/MWh and 174 €/MWh on average, depending on legislation and opposition towards onshore wind installations. By paying a premium of up to 50% compared to the grid-dependent system, 3945 municipalities with 17.2 million inhabitants could become completely autonomous by 2045. For regions that could achieve an autonomous energy supply at moderate costs, however, lost revenues through energy exports could be a decisive argument against autonomy efforts. • Single energy system optimizations for 11003 German municipalities. • Assessment of various scenarios in more than one million techno-economic optimizations. • Utilization of high-performance computing clusters for parallelized optimizations. • Complete energy autonomy technically feasible in 90% of German municipalities. • Extended economic potential for autonomy in 36% of German municipalities. [ABSTRACT FROM AUTHOR]

• Analysis of hydrothermal potential in German municipalities. • Optimisation of simultaneous geothermal heat and electricity generation. • Drilling depth and hydrothermal temperature are implemented endogenously. • Integration of geothermal plants in a holistic energy system optimisation. • Geothermal plants reveal a potential for cost reduction in off-grid municipalities. A growing number of German municipalities are striving for energy autonomy. Geothermal plants are increasingly constructed in municipalities in order to exploit the high hydrothermal potential. This paper analyses the potential contribution of simultaneous geothermal power and heat generation in German municipalities to achieving energy autonomy. A linear regression estimates the achievable hydrothermal temperatures and the required drilling depths. Technical restrictions and cost estimations for geothermal plants are implemented within an existing linear optimisation model for municipal energy systems. Novel modelling approaches, such as optimisation with variable drilling depths, are developed. The new approach is validated with data from existing geothermal plants in Germany, demonstrating a Root Mean Squared Error of about 15%. Eleven scenarios show that achieving energy autonomy is associated with at least 4% additional costs, compared to scenarios without it. The crucial role of geothermal plants in providing base load heat and power to achieve energy autonomy is demonstrated. The importance of simultaneous modelling of electricity and heat generation in geothermal plants is also evident, as district heating plants reduce the costs, especially in municipalities with high hydrothermal potential. Further work should focus on the optimal spatial scale of the system boundaries and the impact of the temporal resolution of the analysis on the costs for achieving energy autonomy. [ABSTRACT FROM AUTHOR]

In the context of the energy transition, municipalities are increasingly attempting to exploit renewable energies. Socio-energetic data are required as input for municipal energy system analyses. This Data Descriptor provides a compilation of 40 indicators for all 11,131 German municipalities. In addition to census data such as population density, mobility data such as the number of vehicles and data on the potential of renewables such as wind energy are included. Most of the data set also contains public data, the allocation of which to municipalities was an extensive task. The data set can support in addressing a wide range of energy-related research challenges. A municipality typology has already been developed with the data, and the resulting municipality grouping is also included in the data set. Measurement(s) Demographic Data • vehicle • renewable energy Technology Type(s) digital curation Sample Characteristic - Environment city Sample Characteristic - Location Germany Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.9933890 [ABSTRACT FROM AUTHOR]

• Development of combinatorial optimisation model to design district heating networks. • Optimisation of the location of the district heating plant in municipalities. • Deep geothermal energy is used as heat source. • Heuristic has high accuracy and is significantly faster than the optimisation. • Applicable for any German municipality and extendable to other locations. Plants increasingly exploit high geothermal energy potentials in German district heating networks. Municipal planners need instruments to design the district heating network for geothermal heat. This paper presents a combinatorial mixed-integer linear optimisation model and a three-stage heuristic to determine the minimum-cost district heating systems in municipalities. The central innovations are the ability to optimise both the structure of the heating network and the location of the heating plant, the consideration of partial heat supply from district heating and the scalability to larger municipalities. A comparison of optimisation and heuristic for three exemplary municipalities demonstrates the efficiency of the latter: the optimisation takes between 500% and 1 × 107% more time than the heuristic. The deviations of the heuristic's calculated total investments for the district heating system compared to the optimisation are in all cases below 5%, and in 80% of cases below 0.3%. The efficiency of the heuristic is further demonstrated by comparison with the Nearest-Neighbour-Heuristic, which is less efficient and substantially overestimates the total costs by up to 80%. The heuristic can also be used to design district heating networks in holistic energy system optimisations due to the novel possibility of connecting an arbitrary number of buildings to the network. Future work should focus on a more precise consideration of heat losses, as well as taking additional geological and topographical conditions into account. [ABSTRACT FROM AUTHOR]