Abstract :
[en] Abstract
As the transition to low-carbon energy systems becomes increasingly urgent, countries and communities worldwide are searching for pathways to achieve this goal through long-term energy planning. As a result, several modelling tools have become available, each tackling issues using distinct approaches or addressing specific aspects of the system’s behavior. Therefore, by considering a common objective and structure, redundancies among models can be used to check consistency and enrich them by including inputs or supplementary information from each other. This research explores the coupling of two energy system optimization models with different levels of detail regarding demand characterization, sector representation, spatial granularity, and temporal resolution to address energy planning challenges at the national level, using Bolivia as its case study. The work makes use of a whole-energy system model (EnergyScope-BO) to provide a comprehensive characterization of the entire energy system and future energy demands, and a power system optimization model (PyPSA-BO), which is used to analyze the expansion of the installed capacity in the future. To exploit the complementarities between both models, a bidirectional linking is proposed, where key outputs from each model are exchanged and iterative runs are made until results from both models converge within a 10% discrepancy margin. The method is applied to analyze two potential development scenarios for the Bolivian case study, and models converge in the total energy production by technology after 5 iterations or fewer. Results for the Bolivian case show that strategic conditions are required to facilitate the transition of its energy system in the long term, such as large financial capabilities, electrification of energy demands, and integration of biomass as a key energy vector, all of which facilitate tackling its current systemic reliance on fossil fuels.
