Three-step modification and optimization of Kalina power-cooling cogeneration based on energy, pinch, and economics analyses

Abstract

Abstract This study proposes a systematic approach for modification and optimization of Kalina power-cooling cogeneration (KPCC) under a three-step procedure. In the first of three steps, KPCC is modeled and optimized thermodynamically by a non-dominated sorting genetic algorithm II (NSGA-II). In the second step, heat pinch analysis (HEPA) modifies the performance of KPCC heat exchangers network (HEN). Finally, the geometries of the heat exchangers are optimized by nonlinear programming (NLP) to minimize the system’s purchasing cost. The results showed that KPCC could achieve thermal and power-cooling efficiencies of 12.1% and 38.6%, respectively. Moreover, the HEN satisfied HEPA constraints with nine exchangers at a minimum temperature difference (DT) of 10 K. By employing NLP, investment costs of the heat exchangers were reduced significantly and the overall investment costs of KPCC decreased by approximately 31%, demonstrating that the three-step procedure can optimize KPCC efficiency while minimizing costs.