Climate-adaptive machine learning-driven analysis of a hybrid parabolic trough collector-based cogeneration system with steam turbine, thermoelectric generator, and phase change material for environmental sustainability

The biggest obstacle to the widespread adoption of solar energy technologies is the impact of regional climatic conditions on production interruptions and performance degradation. This study presents a novel artificial intelligence (AI)-assisted simulation framework that analyses the techno-economic feasibility of an experimentally validated hybrid parabolic trough collector (PTC), steam turbine, thermoelectric generator (TEG), and phase change material (PCM) system across Türkiye. Within the scope of the study, high-resolution meteorological data (2005–2023) from 11 different provinces are processed, and the system’s thermal losses due to temperature and wind are modelled with dynamic correction factors. The developed k-means clustering algorithm classifies the provinces according to their investment potential, and an autonomous decision mechanism is implemented for each region, switching between 6-bar (TEG-driven) and 14-bar (turbine-driven) operating modes. Simulation results indicate that the proposed AI-based dynamic operating strategy enhances annual energy production by 22.7%, particularly in regions with low insolation potential, such as Istanbul, and transitions the system from an idle state to an economically viable state. In regions with high potential (e.g. Antalya and Van), the system’s levelised cost of energy (LCOE) is reduced to $0.04/kWh, while payback periods are mitigated to less than 3.5 years with the inclusion of carbon tax revenues under the EU Green Deal (CBAM). Residential-scale scenario analyses highlight that the hybrid system reaches the capacity to meet 100% of household demand in the summer months, selling energy to the grid, and minimising its water footprint. This study serves as a national roadmap demonstrating the applicability of hybrid solar systems not only on the southern coast but also in challenging climate zones.