Thermo-economic evaluation of working fluids for a flue gas driven organic Rankine cycle powered vapor compression cycle for cooling air conditioning using a two-step intermediate performance index

In this study, the thermo-economic evaluation of flue gases driven organic Rankine cycle (ORC) powered vapor compression chiller (VCC) has been conducted. The multi-objective optimization was conducted by first obtaining the Artificial Neural Network (ANN) to obtain the total exergy destruction $\left({\mathrm{Ed}}_{\mathrm{tot}}\right)$ and total heat transfer capacity of all the heat exchanger ${(UA}_{\mathrm{tot}})$. Afterwards, the optimization by applying the Genetic Algorithm (GA) together with Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was carried out. Subsequently, at the optimized point, the operating parameters obtained were used to obtain the ANN regressed equations for the shell and tube type, and flat plate heat exchanger area and pressure drops. The obtained equations were further used to optimize these entities using Genetic Algorithm and the TOPSIS to acquire the total investment costs. This two-step process enables the comprehensive yet computationally manageable multi-objective optimization of the thermal systems of similar nature. From the research conducted, the Decane ORC powered R600a VCC was found to be the feasible candidate with the total exergy destruction and the payback period of 24.50 kW and 7.25 years, respectively.