Exergy-Based Optimization of a CO2 Polygeneration System: A Multi-Case Study

A polygeneration system for power, heat, and refrigeration has been evaluated and optimized using exergy-based methods. CO2 is the working fluid. The study considered two environmental conditions for the potential implementation of the polygeneration system: cold (Case(cold)) and hot (Case(hot)). Aspen HYSYS (R) was used to perform steady-state simulations, Python was used for the automation of the process, and the connection of Aspen HYSYS (R) with Python was successfully applied for single-objective and multi-objective optimizations. A wide range of decision variables was implemented. The minimization of the average cost of a product per unit of exergy was the goal of single-objective optimization and was included in the multi-objective optimization in addition to the maximization of the overall exergy efficiency. Single-objective and multi-objective optimization were applied. Both optimization algorithms result in the necessity to increase the pinch temperature in the heat exchanger (Delta T-pinch,T-HE), maintain the pinch temperature in the gas cooler (Delta T-pinch,T-GC), and augment this value for the evaporator (Delta T-pinch,T-EVAP). Notably, higher isentropic efficiency for turbomachinery correlates with improved optimization outcomes. These findings contribute to the applicability and performance of the polygeneration system, offering potential advancements in sustainable energy solutions.