The aim of the project was to develop transformation pathways for the energy system that minimize raw material risks while simultaneously meeting greenhouse gas emission targets. To this end, highly aggregated criticality indicators were developed from both a market-based (K_Econ) and geopolitical (K_Geo) perspective, based on empirical and model-based data, and for the first time integrated consistently into an energy system optimization model (REMix). In addition, material flow models were developed to determine global raw material demands accounting for recycling potentials, and multi-criteria optimization methods — in particular the parallelizable Augmented Epsilon Constraint approach — were implemented to identify compromise solutions between competing objectives.

Key Results

The results demonstrate that raw material-related risks can influence the optimal technology selection and the structure of future energy systems — yet can in many cases be significantly reduced through targeted measures without incurring substantial additional costs. With this integrated approach, a significant research gap has been closed, as raw material aspects of transformation strategies had previously been assessed predominantly as an afterthought. Raw material criticality, recycling potentials, and supply risks can now be incorporated directly into long-term energy system planning, thereby strengthening the resilience of future energy systems against supply disruptions and providing new scientific foundations for a resource-efficient energy transition.