Numerical evaluation on energy saving potential of the photovoltaic fresh air preheating system in different climate regions of China

•A dynamic model of photovoltaic fresh air preheating system is established.•The energy saving potential of the system under different climate is analyzed.•Lhasa has the highest monthly average total energy efficiency, reaching 52.47%.•The monthly average total energy efficiency of the other cities is higher than 35%. The fresh air system in buildings consumes a large amount of energy. To preheat fresh air by using solar energy can effectively reduce the energy consumption of buildings. This paper combines photovoltaic thermal system with air handling unit (AHU) fresh air system to supply buildings with fresh air, and the combined system utilizes photovoltaic (PV) cells to generate electricity while preheating the fresh air at the same time. Based on the control-volume method and zonal approach, a dynamic model suitable for simulating the PV fresh air preheating system in real operating conditions was developed in this paper. A PV fresh air preheating system test platform was set up and tested in Changsha. The model was validated by the data collected under real conditions and the simulated results show a good agreement with the experimental data. The performance of the PV fresh air preheating system and its energy saving potential in four typical cities in different climate regions, Changsha, Beijing, Shenyang and Lhasa respectively, were analyzed. Results show that the performance of the PV fresh air preheating system is mainly affected by the solar radiation. The application of the system in Lhasa can reach the highest energy saving potential among the researched cities, followed by Shenyang and Beijing. Due to the high ambient temperature and poor solar radiation, the monthly average total energy efficiency of Changsha is the lowest among the four cities. The results can provide a theoretical guidance for the application of the PV fresh air preheating system in different climate regions of China.