Performance Optimization of a Transcritical CO2 Supermarket Refrigeration System Equipped with an Ice Tank Unit and a Photovoltaic System

CO2 has been considered as a refrigerant for commercial use because of its low environmental impact. However, due to low critical temperature of CO2, refrigeration systems that utilize this refrigerant mostly work in transcritical regime, resulting in decreased efficiency and higher energy consumption. This thesis proposes a method to optimize the performance of a transcritical CO2 vapour compression single-stage supermarket refrigeration system equipped with an ice tank unit and a photovoltaic system. In particular, the project will focus on the optimization of the ice tank usage. The ice tank reduces the temperature of the CO2 exiting the gas cooler of the transcritical system to decrease the power consumption of the cycle. However, as the ice tank is used the ice melted should be recovered so that the ice tank can be used again. The charging of the ice tank (which is done by a R290 cycle in this project) increases the total power consumption and creates a trade-off between discharging (ice melt), and charging (ice build). In certain operating conditions, the photovoltaic system may generate surplus energy that can be used to charge the ice tank at zero cost, which is certainly desirable. This project proposes a fully automated model-based control strategy based on Nonlinear Model Predictive Control (NMPC). The NMPC controller solves the optimization problem at run-time, allowing for a superior robustness to model uncertainties with respect to strategies based on offline optimization. The results showed a predicted average annual energy saving of 4.912 MWh (2.26%), 2.343 MWh (2.59%) in a year in New Delhi (India) and Sydney (Australia), respectively.