Modeling and Analysis of Least-Cost Electrification using a Custom Python Tool and Monte Carlo Simulations

Abstract

Achieving universal energy access in remote and rural regions such as Antongil Bay is a key challenge that is aligned with Sustainable Development Goal 7 (SDG7), which aims to ensure access to affordable, reliable and sustainable energy for all. This study, which is designed to assist the project ”Promotion of Rural Electrification through Renewable Energies” (PERER) by the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ), provides a comprehensive analysis of electrification strategies to inform policymakers, development organizations, and local stakeholders. The analysis employs geospatial data, clustering algorithms, and Levelized Cost of Electricity (LCOE) calculations to determine the most cost-effective technology mix. The study uses a discounted cash flow model, based on assumptions specific to the technology in question, to calculate the LCOE. A Monte Carlo simulation with 5,000 iterations captures uncertainty by assigning triangular distributions to key inputs such as CAPEX and connection rates. A sensitivity assessment was conducted by employing Spearman’s correlation coefficient to identify the most influential parameters. This approach provides a robust, probabilistic estimate of LCOE outcomes tailored to the local context. A cost-sharing model is applied to optimize grid extension costs, ensuring an equitable distribution of infrastructure expenses among connected households. The results indicate that, while grid extensions require significant upfront investment, they offer the lowest long-term costs per kilowatt-hour in high-density areas. Mini-grids are identified as a viable solution for medium-density communities, whereas SHS remain the most practical option for sparsely populated areas, despite their higher per-unit costs. The study emphasizes the financial and logistical challenges in the electrification process and underscores the importance of tailored approaches to infrastructure development. The proposed framework is designed to function as a decision-support tool to facilitate the achievement of sustainable and cost-effective energy access solutions in Antongil Bay and analogous regions, thereby contributing to the broader objectives of Sustainable Development Goal 7 and sustainable rural development.