Multi-Objective Optimization of a Solar Combined Power Generation and Multi-Cooling System Using CO2 as a Refrigerant

Abstract

This paper proposes a new combined multi-cooling and power generation system (CMCP) driven by solar energy. Carbon dioxide is used as a refrigerant. A parabolic trough collector (PTC) is employed to collect solar radiation and convert it into thermal energy. The system includes a supercritical CO2 power system for power production and an ejector refrigeration system with two ejectors to provide cooling at two different evaporating temperatures. The CMCP system is simulated hourly with weather conditions for Tunisia. The PTC mathematical model is used to calculate the heat transfer fluid outlet temperature and the performance of the CMCP system on a specific day of the year. A 1D model of an ejector with a constant area is adopted to evaluate the ejector performance. The system’s performance is evaluated by an energetic and exergetic analysis. The importance of the system’s components is determined by an exergoeconomic analysis. The system is modeled using MATLAB software. A genetic algorithm is used for multi-objective optimization to determine the best values and solutions for the system’s design parameters. The optimal energy and exergy efficiencies were found to be 13.7 percent and 37.55 percent, respectively, and the total product unit cost was 31.15 USD/GJ.

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“…The smallest cluster, only 31 entries. Thermal-to-electrical energy conversion problems This paper [42] proposes a new combined multi-cooling and power generation system (CMCP) driven by solar energy. The PTC mathematical model is used to calculate the heat transfer fluid outlet temperature and the performance of the CMCP system on a specific day of the year.…”

Interdisciplinary Studies of Jet Systems using Euler Methodology and Computational Fluid Dynamics Technologies

“…Ejectors are widely applied in mechanical engineering, aerospace, and power engineering [28][29][30], including carbonfree technologies [31,32]. Bencharif et al [33] and Chen et al [34] used AI for optimal ejector design.…”