Combined assessment of material and energy supply risks in the energy transition: A multi-objective energy system optimization approach

Abstract

This paper proposes a novel framework to study the trade-off between different energy transition supply risks through multi-objective energy system optimization. While the increasing use of clean energy technologies reduces reliance on fossil fuels imports and hence energy supply risks, these technologies depend heavily on critical raw materials, the supply chains of which present high geographical concentration and political instability. Current energy system planning lacks endogenous evaluations (e.g., minimization) of such supply risks. To address this gap, two consistent supply risk functions are derived considering concentration, import reliance, and political stability of supply chains of critical raw materials on the one hand and energy commodities on the other hand. We enhance the open-source energy system modeling framework TEMOA by multi-objective optimization using the AUGMECON method to consider these functions endogenously as objectives and demonstrate the capabilities of this new approach for the Italian power sector decarbonization by 2050. First, total system cost and CO₂ emissions are minimized to establish a baseline. Then, four multi-objective optimizations between material and energy supply risks are conducted, each allowing for increasing total system cost. This approach allows the underlying energy system to adapt to minimize supply risks. Results highlight a significant trade-off between the two risks. Minimizing the material supply risk increases energy supply risk by reducing investments in wind turbines and batteries. These technologies are replaced by solar PV and natural gas plants with CCS, which raises gas imports and energy supply risk. Higher costs lead to wind energy disappearance, replaced mainly by natural gas plants, increasing reliance on CCS and imports. These findings emphasize the importance of balancing material and energy supply risks in energy system planning.