The decarburization and reliable electrification of remote railway and mining infrastructure remain critical challenges, particularly in regions with limited grid access. This study develops a spatial optimization framework for hybrid solar photovoltaic and battery energy storage system microgrids along the Lobito Corridor. The methodology integrates geospatial analysis, resource assessment, and techno-economic optimization to determine optimal system sizing, siting, and operation. Multi-objective optimization techniques minimize the Levelized Cost of Energy and Net Present Cost while ensuring system reliability and reducing carbon emissions. The modelling framework incorporates solar irradiance data, load demand profiles, and storage performance parameters, using optimization algorithms to evaluate multiple system configurations. Preliminary findings suggest that optimized PV-battery microgrids significantly reduce reliance on diesel generation, lowering both operational costs and CO₂ emissions while improving energy resilience. Early results also indicate favourable trade-offs between capital investment and long-term savings in remote infrastructure applications. The study’s implications support sustainable energy planning for infrastructure corridors in developing regions. The study focuses on refining demand modelling, integrating dynamic operational strategies, and assessing system sensitivity to key uncertainties