Planning-Based Framework for Long-Term Demand Forecasting and Investment Prioritization in Multi-Regional Microgrid Deployment

As energy systems become more decentralized, microgrids offer a reliable solution for improving resilience in developing regions with limited infrastructure. A major challenge is selecting priority locations. This study presents a method that ranks nodes using demand forecasting, spatial relevance, and investment metrics in data-constrained systems. Demand is estimated with a log-linear model, and financial viability is assessed through Net Present Value (NPV), Levelized Cost of Energy (LCOE). A Spatial Demand Ratio (SDR) is introduced to quantify the contribution of each node. These indicators are combined into a multi-criteria decision-making function that enables prioritization without complex optimization. The approach is applied to ten distribution nodes in Cochabamba, Bolivia. Results show that high demand do not always ensure strong returns, highlighting the need for balanced planning. The model provides a scalable and replicable tool for decentralized energy planning.