Energy system models have become crucial to assess the effectiveness of possible energy policies in pursuing the declared environmental objectives. Among bottom-up models, the tools most widely used by researchers and institutions to perform scenario analyses and policy evaluations rely on commercial software and closed databases, limiting the transparency of the studies. The purpose of this work is to demonstrate that open-source tools, relying on open databases, can be used as a valid alternative to commercial tools, getting equivalent results not only for simple case studies as done so far, but also for complex (national, regional, or multi-regional) reference energy systems. Working on the already available open TEMOA optimization framework, a bottom-up technology-rich model is developed here for the Italian reference energy system on an extended TEMOA version, comparable in detail and complexity to the equivalent TIMES framework. The accuracy of the novel TEMOA-Italy model in a business-as-usual scenario is assessed, showing that the average relative differences with respect to the consolidated TIMES-Italy results are in the order of few percent. The open-source model, available on Github, is now ready for the test and implementation of new optimization paradigms, which was not possible in the TIMES framework.

The European Roadmap towards the production of electricity from nuclear fusion foresees the potential availability of nuclear fusion power plants (NFPPs) in the second half of this century. The possible penetration of that technology, typically addressed by using the global energy system EUROFusion TIMES Model (ETM), will depend, among other aspects, on its costs compared to those of the other available technologies for electricity production, and on the future electricity demand. This paper focuses on the ongoing electrification process of the transport sector, with special attention devoted to road transport. A survey on the present and forthcoming technologies, as foreseen by several manufacturers and other models, and an international vehicle database are taken into account to develop the new road transport module, then implemented and harmonized inside ETM. Following three different storylines, the computed results are presented in terms of the evolution of the road transport demand in the next decades, fleet composition and ${\mathrm{CO}}_2$ emissions. The ETM results are in line with many other studies. On one hand, they highlight, for the European road transport energy consumption pattern, the need for dramatic changes in the transport market, if the most ambitious environmental goals are to be pursued. On the other hand, the results also show that NFPP adoption on a commercial scale could be justified within the current projection of the investment costs, if the deep penetration of electricity in the road transport sector also occurs.

Energy system models for the analysis of future scenarios are mainly driven by the set of energy service demands that define the broad outlines of socio-economic development throughout the model time horizon. Here, the long-term effects of the COVID-19 pandemic on the drivers of the industrial production in six energy-intensive subsectors are addressed using Vector AutoRegressive models. The model results are computed either considering or not considering the effects of the pandemic. The comparison to established pre-pandemic trends allows for validating the robustness of the selected model. The anticipated effect of the pandemic to 2040 shows a long-term reduction by 3% to 10%, according to the different subsector, in the industrial energy service demand. When the computed service demands are used as input to the TIMES-Italy model, which shows good capability to reproduce the energy consumption of the industrial sectors in the period 2006–2020, the impact of the pandemic on energy consumption forecasts can be assessed in a business-as-usual scenario. The results show how the long-term effects of the shock caused by the pandemic could lead, by 2040, to a total industrial energy consumption 5% lower than what was foreseen before the pandemic, while the energy mix remains almost unchanged.