Novel supercritical CO2-Based Low-Carbon multigeneration System: Multi-Objective optimization for combined Power, Cooling, Heating, and desalination

Abstract

The challenges posed by power shortages, hot climates, heating demands, and water scarcity on island platforms significantly impede productivity and quality of life. Implementing a multi-energy supply system emerges as a promising solution to address these issues. In this study, we propose, analyze, and optimize a novel multigeneration system for cooling, heating, power, and desalinated water production, leveraging waste heat from a nuclear power plant. This innovative system integrates a recompression supercritical CO₂ (sCO₂) Brayton cycle, an Organic Rankine Cycle (ORC) with a booster-enhanced ejector refrigeration cycle (BERC), an absorber heat transformer (AHT) with a distillation unit, and a heating unit (HU). Harnessing energy cascading from nuclear power, the system efficiently recovers surplus heat generated by the sCO₂ cycle, which serves multiple purposes: powering the ORC generator for additional power generation, driving the BERC for user cooling, and fueling the AHT and HU systems for freshwater production and user heating, respectively. The system’s performance is rigorously evaluated through thermodynamic and exergoeconomic analyses, leveraging established and validated models. Parametric analysis reveals crucial trends in system performance with respect to eight key parameters. Additionally, single-objective and multi-objective optimizations, utilizing a weight coefficients approach, are conducted to maximize thermodynamic efficiency and minimize total product unit cost. Notably, the importance of balancing the sCO₂ compressor pressure ratio for optimal exergy efficiency or minimum total product cost is underscored. Exergoeconomic optimization demonstrates a substantial reduction (6.1% and 1.59%) in the overall cost of unit product compared to energy and exergy efficiency optimizations alone, while achieving optimal energy efficiency (62.54%), exergy efficiency (66.75%), and a sum unit cost of products of 10.02 $/GJ. Multi-objective optimization, treating all three objectives equally, yields impressive results, including an energy efficiency of 82.3%, exergy efficiency of 62.41%, and a sum unit cost of products of 10.58 $/GJ.