Abstract
Geomorphological stratification of the territory is rarely integrated explicitly into sizing models for hybrid solar-wind energy matrices, even though relief modulates both resources in opposite ways. This work proposes a four-stage model that combines geomorphological stratification by elevation ranges, resource-specific solar and wind characterization, a decision-tree surrogate model that reproduces the coupled physical simulation (PVWatts and the Jensen wake model) with high fidelity (R² > 0.99), and optimization through mixed-integer linear programming (MILP). MILP is subject to a hybridization constraint that prevents a single technology from occupying more than 80% of the installed area. The model was applied to a first geographical location, including four altitudinal strata, and subsequently contrasted with a second one. For the first site, the wind resource was non-viable across all strata, and the model consistently selected exclusively solar configurations. At the second location, in contrast, it autonomously proposed the construction of a real hybrid matrix with a 73% wind and 27% solar contribution. The same procedure, without external reparameterization between territories, adapted the technological composition to the local resource of each territory, which constitutes the main evidence of the ability of the model to be generalized across territories with diverse resource conditions.