Abstract
This article analyzes and compares three methodologies for identifying suitable regions for solar hydrogen production using photovoltaic panels: AHP (Analytic Hierarchy Process), FAHP (Fuzzy Analytic Hierarchy Process), and MC-FAHP (Monte Carlo FAHP), integrated with GIS (Geographic Information Systems). The study employs ten criteria across technical (Global Horizontal Irradiance, temperature, slope, elevation, orientation), economic (distance from transportation and electrical networks), and social (population density, proximity to residential areas) factors. Environmental and exclusion criteria define restrictive zones. The analysis reveals that while all three methods agree on areas of low suitability, they diverge in their classification of "Suitable," "Highly Suitable," and "Most Suitable" regions. FAHP identifies 229.573 km(2) as "Highly Suitable," compared to AHP's 222.048 km(2) and MC-FAHP's 230.299 km(2) for "Suitable" areas. Despite these differences, the energy potential is consistent across methods, totaling around 79,000 TWh/year, with MC-FAHP estimating the highest hydrogen production potential at 1.51 billion tons/year. The study concludes that fuzzy-based methods (FAHP and MC-FAHP) better handle uncertainties than traditional AHP. The MC-FAHP method, in particular, performs well in managing stochastic variability and yielding more reliable results. The findings are validated through a case study in Guider and Maroua, highlighting the importance of socio-economic and environmental criteria in decision-making. A sensitivity analysis reveals that economic and social criteria significantly influence land suitability, underscoring the importance of criteria selection in decision-making.