Volume 39: Energy Transitions toward Carbon Neutrality: Part II

CO2 Heat Pump for Simultaneous Cooling and Heating: Enhancing Efficiency through Model Predictive Control and Neural Network Identification Jintao He, Yu Yao, Meiyan Zhang, Yonghao Zhang, Bowen Lu, Lingfeng Shi, Gequn Shu

Abstract

The carbon dioxide heat pump for simultaneous heating and cooling is an exceptional technology; however, current research tends to excessively prioritize the overall system efficiency improvement, neglecting the alignment of the system with heating and cooling supply and demand. This oversight leads to the wastage of redundant heat or cold in practical applications, resulting in energy loss. Therefore, addressing this from a supply-demand perspective, this study proposes a model predictive control based on demand. It integrates a novel carbon dioxide heat pump structure to mitigate the loss of redundant energy. Furthermore, this approach utilizes neural network identification to reduce the online computational load of the model predictive control in the carbon dioxide heat pump system.

Keywords carbon dioxide; simultaneous cooling and heating; model predictive control; neural network identification