The Bolivian government’s concerns that are related to reducing the consumption of diesel fuel, which is imported, subsidized, and provided to isolated electric plants in rural communities, have led to the implementation of hybrid power systems. Therefore, this article presents the performance analysis in terms of energy efficiency, economic feasibility, and environmental sustainability of a photovoltaic (PV)/Stirling battery system. The analysis includes the dynamic start-up and cooling phases of the system, and then compares its performance with a hybrid photovoltaic (PV)/diesel/battery system, whose configuration is usually more common. Both systems were initially optimized in size using the well-known energy optimization software tool, HOMER. An estimated demand for a hypothetical case study of electrification for a rural village of 102 households, called “Tacuaral de Mattos”, was also considered. However, since the characteristics of the proposed systems required a detailed analysis of its dynamics, a dynamic model that complemented the HOMER analysis was developed using MATLAB Simulink TM 8.9. The results showed that the PV/Stirling battery system represented a higher performance option to implement in the electrification project, due to its good environmental sustainability (69% savings in CO₂ emissions), economic criterion (11% savings in annualized total cost), and energy efficiency (5% savings in fuel energy conversion).

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.

Reaching carbon neutrality by mid-century requires energy system models that jointly capture long-term investment and regional differences in resources and infrastructure. This paper presents EnergyScope Multicell Pathway (ESMC Pathway), a new open-source linear-programming framework combining multi-regional resolution, hourly granularity, and multi-decade pathway optimization. Its detailed end-use representation further accounts for age-based technology decommissioning, a dual pipeline-freight scheme for liquid fuels, and differentiated treatment of interconnected versus off-grid regions. Optimal regional aggregation is determined through replicable K-medoids archetype clustering with three validation metrics (Elbow, Silhouette, Gap statistic). The framework is applied to Bolivia's energy transition under a net-zero emissions scenario where total primary energy supply approximately doubles from 2021 to 2050, while installed power capacity increases ninefold (3.83 to 33.88 GW), led by solar photovoltaics, wind, and hydropower. The transition requires 33.3 b€2021 in new investment (2025-2050) and 51.1 b€2021 in operational expenditure (2021-2050). At full hourly resolution, the six-region pathway takes 9.9 h under perfect foresight and 4.7 h under a myopic rolling horizon; to reduce computational effort further, relaxing the intra-day resolution from 24 to 12 segments per typical day lowers it to 1.1 h, changing optimal cost by only 0.1 % (root-mean-square). A systematic comparison against a single-region formulation shows that multi-regional modeling identifies more wind at cost-competitive high-yield sites, incurring 13 % higher capital and 10 % higher operational expenditure from fleet differences and spatially resolved infrastructure. Spatial detail built into a transition model shapes not just how much is invested, but where and when.