Hierarchical approach to energy system modelling: Complexity reduction with minor changes in results

The energy transition plays a crucial role in the ongoing process of defossilisation and carbon emissions reduction. Considering the substantial cost of the transition and importance of the energy system for the global economy, the transition must be accurately modelled to allow future system development analyses and discus-sions to avoid stranded investments and guarantee a reliable energy supply at every transition step. Energy system models must be operated with a technology-rich portfolio in high temporal and spatial resolution to properly estimate the impact of renewable energy variability and the role of storage and sector coupling tech-nologies. Consequently, modern energy system models comprise tens of millions of variables and constraints, and demand vast computational resources for optimisation. This study proposes a hierarchical approach to run simulations based on partial regional disaggregation as a solution to decrease computational time without sig-nificant change in the modelling results. The discussed method is tested on the case of Japan and shows that the hierarchical approach allows for a reduction in computational time by a factor of 2.3-3.3 compared to the full spatial resolution simulation approach, while the installed capacities and costs of the energy system stay within a +/- 3% range for all steps of the transition through 2020 to 2050.

Automated summary

The energy transition is crucial for defossilisation and carbon emissions reduction. Accurate modeling of the transition is necessary to avoid stranded investments and ensure a reliable energy supply. Modern energy system models require vast computational resources due to their complexity. This study proposes a hierarchical approach that significantly reduces computational time without affecting the modeling results.