Chile’s commitment to achieve carbon neutrality by 2050 underscores the need for robust decarbonization strategies across various sectors. Despite making progress in integrating renewable energy, sectors like transportation and residential heating, which are heavily reliant on fossil fuels, present significant opportunities for decarbonization. This study develops and evaluates pathways based on Chile’s Long-Term Energy Plan for assessing the effect of flexibilities from the power-to-heat and power-to-transportation sectors. Using EnergyPLAN, we model different scenarios of Chile’s 2050 energy plan that incorporate varying levels of individual heating and electromobility and assess their impacts on excess (surplus) electricity generation, different cost metrics, and renewable energy penetration. Findings indicate that increasing flexibility within the transportation sector through smart charging and vehicle-to-grid technologies can reduce excess generation, enhance grid stability, and lower operational costs. Flexibilities in individual heating, when coupled with more renewable energy capacity, show the potential to decrease reliance on fossil fuels significantly. The evidence of major efficiency gains in Chile’s 2050 energy plan, which is achievable by investing in heating and transportation flexibilities and further augmented by the country’s unique renewable potential, should interest stakeholders. Future work will focus on optimizing these technologies to address Chile’s specific infrastructure and regulatory challenges.

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.