Work

A GCC Evidence-Calibrated Nonlinear Decision Framework for Photovoltaic Technology Selection Under Coupled Desert Environmental Stress

Year: 2026

Type: article

Abstract: Photovoltaic technology selection in Gulf Cooperation Council (GCC) desert environments is affected by coupled dust, thermal, ultraviolet (UV), humidity and salinity stresses, which are not fully represented by static weighting and additive multi-criteria decision-making models. This study develops a GCC-calibrated nonlinear decision-support framework that integrates field-based environmental calibration, adaptive hybrid entropy–desert weighting and bipolar fuzzy Einstein aggregation. The framework is applied to compare PERC, TOPCon and heterojunction (HJT) photovoltaic technologies using calibrated evidence from Qatar, the United Arab Emirates, Saudi Arabia and Oman. Results show that dust tolerance receives the highest final hybrid weight (0.258), followed by thermal resistance (0.228), UV resistance (0.207), efficiency (0.173) and cost effectiveness (0.134). The nonlinear Einstein aggregation ranks HJT first (0.889), followed by TOPCon (0.861) and PERC (0.742). Benchmark comparison with TOPSIS, VIKOR and PROMETHEE II shows high rank agreement, while Monte Carlo perturbation analysis indicates that HJT preserves the first rank in 93% of scenarios. The proposed framework links PV technology selection with measured GCC desert stress behavior and provides a reproducible basis for technology prioritization in harsh solar-energy deployment environments.

Source: Energies

DOI: 10.3390/en19163908