Multi-objective Optimization of a Solar Driven Combined Power and Refrigeration System Using Two Evolutionary Algorithms Based on Exergoeconomic Concept

Abstract

This paper deals with a multi-objective optimization of a novel micro solar driven combined power and ejector refrigeration system (CPER). The system combines an organic Rankine cycle (ORC) with an ejector refrigeration cycle to generate electricity and cold capacity simultaneously. Major thermodynamic parameters, namely turbine inlet temperature, turbine inlet pressure, turbine back pressure, and evaporator temperature are selected as the decision variables. Three objective functions, namely the energetic efficiency, exergetic efficiency and cost rate of products are selected for optimization. NSGA-II and MOPSO are employed and compared, to achieve the final solutions in the multi-objective optimization of the system operating. It is found that the values of the energetic and exergetic efficiencies increase within 27.7% and 26.1%, respectively and the cost rate of products decreases by about 32.7% with respect to base case.