Comparative thermoeconomic optimization of hybrid Kalina and dual-ejector organic flash cycles for geothermal power generation

Efficient utilization of low- and medium-temperature geothermal energy remains a key challenge in sustainable power generation. This study presents a comprehensive thermodynamic and exergoeconomic comparison of two novel hybrid configurations: the KCS-11–DE-OFC and KCS-34–DE-OFC systems, in which the Kalina Cycle Systems (KCS-11 and KCS-34) are integrated with a Dual-Ejector Organic Flash Cycle (DE-OFC). Detailed thermodynamic modeling, exergy analysis, and cost evaluation were conducted using Engineering Equation Solver (EES), and results were optimized through a multi-objective genetic algorithm (GA) coupled with an artificial neural network (ANN) surrogate model. Parametric analysis revealed that turbine inlet pressure and ammonia mass fraction are the most sensitive parameters affecting system efficiency. Crucially, the addition of the DE-OFC bottoming cycle provides a substantial performance enhancement. Compared to standalone Kalina baselines operating under identical conditions, the DE-OFC integration yields an absolute exergy efficiency improvement of 6.79% for the KCS-11 architecture and 6.46% for the KCS-34 architecture. Ultimately, the integrated KCS-34–DE-OFC system achieved a maximum exergy efficiency of 46.45% and a net power output of 480.8 kW, while the KCS-11–DE-OFC attained 40.79% exergy efficiency with a net power output of 484.4 kW. However, KCS-11–DE-OFC exhibited a lower unit product cost (36.39 $/GJ) compared to KCS-34–DE-OFC (45.86 $/GJ), indicating superior economic feasibility. The combined GA–ANN framework successfully identified optimal trade-offs between performance and cost, suggesting that KCS-11–DE-OFC is preferable for cost-sensitive applications, whereas KCS-34–DE-OFC is ideal when maximizing efficiency is prioritized.