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

Abstract

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 (Casecold) and hot (Casehot). Aspen HYSYS® was used to perform steady-state simulations, Python was used for the automation of the process, and the connection of Aspen HYSYS® 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 (ΔTpinch,HE), maintain the pinch temperature in the gas cooler (ΔTpinch,GC), and augment this value for the evaporator (ΔTpinch,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.

Keywords

• heat recovery
• solar energy
• CO₂
• polygeneration
• exergy-based method
• optimization