Towards resilient energy decisions: Integrating scenario-based weighting and Monte Carlo sensitivity in hybrid renewable system selection in Algeria

• A comprehensive MCDM analysis was conducted to select the optimal renewable energy system in Algeria. • The research innovatively integrated SAW and TOPSIS methods with full sensitivity analysis. • Technical, economic, environmental, and social criteria were all considered in the evaluation. • The solar system in Tamanrasset, with very low cost and zero CO₂ emissions, was identified as the best option. • The proposed framework can serve as an effective tool for energy transition planning Given the challenges of ensuring sustainable energy supply across different regions of Algeria and the need to reduce reliance on fossil fuels, this study presents a comprehensive framework for evaluating and ranking hybrid renewable energy systems. In two climatically and resource-wise distinct regions (Tamanrasset and Adrar), techno-economic simulations were conducted using HOMER software, and multi-criteria decision-making (MCDM) analysis was performed based on the SAW and TOPSIS methods. Seven key criteria—including initial cost, levelized cost of electricity (LCOE), payback period, renewable energy production, energy losses, CO₂ emissions, and population coverage—were evaluated. The results showed that the Tamanrasset option, with a fully solar-based structure, zero CO₂ emissions, an LCOE of $0.225 per kilowatt-hour, and a payback period of 0.29 years, ranked first in five out of six defined scenarios. In contrast, the Adrar option, based on a wind/diesel structure with annual production of 7,425 kWh, ranked first only in the performance-focused scenario. Monte Carlo sensitivity analysis with 5,000 iterations revealed that Tamanrasset remained the top choice in over 99% of cases. The proposed framework, by integrating scenario analysis, uncertainty assessment, and multi-criteria modeling, serves as an effective tool for decision-making in clean energy transition projects.