Implications of defining exogenous variables in Energy System Modeling with Integrated Assessment Models for transition planning

The sustainable transition of energy systems heavily relies on models that provide diverse scopes and applications. This study explores how two modeling approaches can work in tandem and complement each other to provide a more robust framework for analyzing the development of energy systems at the country level. Specifically, we consider an Integrated Assessment Model (GCAM), to evaluate alternative transition scenarios in a country from a multi-sectoral level, and an Energy System Model (PyPSA-Earth), to optimize the expansion of the power system with high geographical and temporal resolution. In this study, we present tailored versions of these tools to analyze Bolivia as the case study, GCAM-Bolivia and PyPSA-BO. Our method employs a unidirectional soft-linking process, using carbon budgets and projected energy demands as the connecting parameters between models. In this sense, GCAM-Bolivia is used to derive six alternative development scenarios based on emission reduction targets until 2050, while PyPSA-BO is used to optimize the electric system expansion, including generation, storage, and transmission capacities. Results show that, regardless of the scenario, solar PV is the dominant technology for capacity expansion in the future and that the growth of the electric sector appears to have a non-linear relation with the emission reduction targets for the energy sector, where only reduction targets above 40% trigger an intensive electrification process. In these cases, a significant expansion of storage and transmission capacities distributed across the country is required to provide flexibility in the system.