Parametric analysis and optimization of CO₂ trans-critical cycle for chiller application in a warm climate

This article presents parametric analysis and subsequent optimization of a CO₂ trans-critical chiller system operating in a warm climate. High side pressure and gas cooler face velocities are two controllable parameters investigated. COP of the system is analyzed and optimized using a developed and validated mathematical model. The mean relative error of prediction in COP is found to be within ±10% for physics-based model and within ±1% for Artificial Neural Network (ANN) based model of the experimental findings. The validated mathematical model is utilized to predict optimal high side pressure as well as gas cooler face velocity for the varying ambient and evaporation conditions to achieve best possible COP. A possibility of 5.31% improvement in COP is found based on the optimization of parameters. The proposed methodology is deemed suitable for design and testing of control system for maximization of energy efficiency.