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Hard-to-electrify sectors will require renewable fuels to facilitate the green transition in the future. Therefore, it is crucial to identify promising production locations while taking into account the local biomass resources, variable renewable energy sources, and the synergies between sectors. In this study, investments and dispatch operations are optimised of a large catalogue of renewable fuel production technologies in the open-source software SpineOpt, and this is soft-linked to the comprehensive energy system model Balmorel. We analyse future production pathways by comparing various levels of hydrogen infrastructure, including large-scale hydrogen storage, and assess system impacts. The results indicate that methanol may provide synergies in its multipurpose use as an early (2030–2040) shipping fuel and later as an aviation fuel through further refining if ammonia becomes more competitive (2050). We furthermore show that a hydrogen infrastructure increases the competitiveness of non-flexible, hydrogen-based fuel production technologies. Offshore electrolysis hubs decrease energy system impacts in scenarios with 105 TWh of Nordic hydrogen export. However, hydrogen export scenarios are much costlier compared to scenarios with no export unless a high hydrogen price is received. Finally, we find that emission taxes in the range of 250–265 €/tCO 2 will be necessary for renewable fuels to become competitive. [Display omitted] • Renewable fuel production is modelled by soft-linking Balmorel and SpineOpt. • Decarbonising Nordic international transport requires emission taxes around 260 €/tCO 2. • Hydrogen infrastructure benefits inflexible, hydrogen-based fuel production. • Methanol, ammonia and Fischer–Tropsch fuels all play a role as future transport fuels. [ABSTRACT FROM AUTHOR]

Energy system modeling is a commonly used method to provide policy recommendations and insight to transformation pathways of energy systems. However, the low open-source availability of the frameworks in practice often leads to low interpretability and transparency of energy modeling system configurations. The configuration of an energy model entails how its system components, such as power plants, storage systems and grids operate, and which parameters are used to define them. In order to understand the impact of different model configurations and working principles on the model output, a thorough comparison between various modeling frameworks is necessary. This work thereby consists of a comparison of five open-source energy system modeling frameworks (OS-ESMFs) oemof , GENeSYS-MOD , Balmorel , urbs and GENESYS-2 on the mathematical level and spotlights selected methodological differences in renewable energy system modeling. The comparison shows diversity in the complexity of selected system components and helps to define the best use-cases and scales of application for each framework. Impacts of modeled features on the results were demonstrated by implementing two harmonized scenarios depicting the German electricity system using each framework. While similar model results were obtained for both scenarios, some differences were present, especially in the long-term expansion planning model. Some of those differences could be traced back to the identified modeling differences. • Selected mathematical features of five open energy modeling frameworks are compared. • A common terminology to facilitate direct mathematical comparison is developed. • Key feature differences are presented to increase transparency of modeling activities. • Influences of the modeling differences on the model results is demonstrated. • The frameworks show various differences, but remain flexible in specific application. [ABSTRACT FROM AUTHOR]