“site suitability analysis for integrating large-scale hybrid photovoltaic and concentrated solar power plants in Cameroon using Monte Carlo, analytic hierarchy process, and geographic information system methods”

• 57.65 % of Cameroon’s land is suitable for hybrid PV-CSP solar power plants. • Theoretical electricity production is 45,069,127 TWh/year using the MC-AHP method. • MC-AHP provided more reliable results than AHP and FAHP. • Sensitivity analysis showed economic and social weighting affect land suitability. • Methodology was validated using real-world solar plants in Guider and Maroua. This study identifies optimal locations for hybrid solar PV-CSP (Photovoltaic-Concentrated Solar Power) plants in Cameroon using a combination of decision-making methods, including AHP (Analytic Hierarchy Process), FAHP (Fuzzy AHP), and MC-AHP (Monte Carlo AHP), alongside GIS (Geographic Information System) for spatial analysis. Twelve critical factors, such as solar irradiation, infrastructure proximity, and population density, were evaluated to assess land suitability for solar energy development. The results revealed that 57.65% of Cameroon’s land is suitable for solar power generation, with a significant portion classified as highly suitable for hybrid PV-CSP systems. The estimated theoretical electricity production potential varied slightly across the methods, ranging from 45,017,186 TWh/year (AHP) to 46,221,626 TWh/year (FAHP) and 45,069,127 TWh/year (MC-AHP), highlighting the substantial energy potential of these hybrid systems. The study also conducted a comparative analysis of the three decision-making methods. While all methods showed similar trends, MC-AHP was found to be the most effective in handling uncertainty, providing more reliable results through Monte Carlo simulations. Additionally, sensitivity analysis was performed to evaluate how different weighting schemes influenced land suitability classifications. It demonstrated that shifting the weights based on economic or social factors altered the land allocation, which emphasizes the importance of aligning decision-making with project priorities. The methodology was validated by comparing the suitability maps with real-world solar plants in Guider and Maroua, which were located in highly suitable areas, supporting the model’s accuracy. This study concludes that Cameroon has significant solar energy potential, and the applied methods offer a robust framework for identifying the best locations for solar power development. Despite challenges such as high initial costs and regulatory barriers, the study provides a solid basis for future solar energy projects. The findings can inform national energy policies, stimulate investment in solar energy, and serve as a model for similar regions.