Discharge pressure is an important factor that heavily affects the system COP in the transcritical CO2 heat pump. In most cases, it is commonly confirmed by the empirical correlations or calculated by the mathematical model according to a single operation condition, thus leading to the prediction error or lengthy time. In this paper, a novel model using the statistical method known as the group method of data handling-type (GMDH) and PSO-BP-type (Particle-Swarm-Optimization and Back-Propagation) neural network was developed to predict the optimal discharge pressure. The relevance of all the parameters to the optimal discharge pressure was investigated orderly. Results showed that the new model had the highest accuracy compared to the current correlations. The relative error was around 1.6% while the error of traditional methods ranged from 11.1% to 44.9%. Therefore, the CO2 heat pump could work better in the optimal COP operation condition with the novel statistical model.
History
Publication title
International Journal of Refrigeration
Volume
106
Pagination
549-557
ISSN
0140-7007
Department/School
School of Engineering
Publisher
Elsevier Sci Ltd
Place of publication
The Boulevard, Langford Lane, Kidlington, Oxford, England, Oxon, Ox5 1Gb