Advanced exergy and exergoeconomic assessment under variable load conditions and multi-objective optimization of a solar-powered kalina cycle: Case study for Tabriz

Abstract

Global warming and the depletion of fossil fuels underscore the need for efficient and sustainable energy conversion systems. This study investigates a solar-driven high-temperature Kalina cycle integrated with molten-salt thermal storage through a combined thermodynamic and exergoeconomic framework. The system is analyzed using energy, conventional and advanced exergy, and exergoeconomic methods under full-load and part-load conditions representative of solar variability in Tabriz. The baseline configuration achieves an energy efficiency of 14.56%, an exergy efficiency of 15.58%, and a net power output of 20,000 kW, with the heliostat field and receiver responsible for about 82% of total exergy destruction. Conventional exergoeconomic analysis identifies the evaporator and turbine as the most cost-intensive components, contributing the highest investment and exergy destruction cost rates. Advanced exergy analysis reveals the turbine as the dominant source of avoidable losses, accounting for 28% of total exergy destruction at part load, while advanced exergoeconomic analysis confirms these two components as primary targets for cost reduction. Multi-objective optimization using the Grey-Wolf algorithm coupled with entropy-based TOPSIS improves energy and exergy efficiencies to 16.33% and 17.47%, increases net power output by 12.2%, and reduces total exergy destruction by 2.05%. The optimized configuration also lowers investment and exergy destruction cost rates by 4.97% and 12.67%, respectively, and decreases the electricity production cost by 8.45%. The results demonstrate that advanced analyses provide deeper insight into component-level inefficiencies and that optimization significantly enhances both the thermodynamic and economic performance of solar-driven Kalina systems.