The transition towards more sustainable, fossil-free energy systems is interlinked with a high penetration of stochastic renewables, such as wind and solar. Integrating these new energy resources and technologies will lead to profound structural changes in energy systems, such as an increasing need for storage and a radical electrification of the heating and mobility sectors. To capture the increasing complexity of such future energy systems, new flexible and open-source optimization modelling tools are needed.

This paper presents EnergyScope TD, a novel open-source model for the strategic energy planning of urban and regional energy systems. Compared to other existing energy models, which are often proprietary, computationally expensive and mostly focused on the electricity sector, EnergyScope TD optimises both the investment and operating strategy of an entire energy system (including electricity, heating and mobility). Additionally, its hourly resolution (using typical days) makes the model suitable for the integration of intermittent renewables, and its concise mathematical formulation and computational efficiency are appropriate for uncertainty applications. We present the linear programming model, detailing its formulation, and we apply it to a real-world case study to discuss advantages and disadvantages in comparison to other modelling frameworks. In particular, we model the national energy system of Switzerland to evaluate a 50% renewable energy scenario.