Photovoltaic/thermal (PV/T) systems play an important role in solar system development, reducing pollution, and meeting the rapid increase in energy demand. PV/T can significantly improve energy transfer efficiency, hence improving its performance attracted extensive research attention. Different structures of the solar collector are proposed. To reduce the investment and cost of the experiment, several prediction studies are also conducted, as modeling its performance is meaningful for the optimization and design of the system.
In this thesis, we study a photovoltaic/thermal assisted air source heat pump (PV/T-ASHP) system with a novel absorber of the solar collector in Beijing. It is shown that for the whole year the electricity self-sufficiency is over 50 % and the heat self-sufficiency is 30.7 % in extreme conditions for the heating systems (e.g., December). Ambient temperature and solar irradiation change highly affect the performance of the whole system. In extreme weather e.g., a sunny day in December, the average COP is higher than 3.5. The payback time for this system is 9.5 years, and it reduces equivalent to 6.8 t of carbon dioxide (CO2) emission per year. Based on the experiment results, we then predict the performance using an ANN. It is seen that the more considered factor, the higher the performance of the prediction model. It is also seen that in this case, an ANN with two hidden layers performs better than that of one hidden layer. Furthermore, the comparison results suggest that in practice it is required to find the best suitable ANN network before application.
|Date of Award||8 Jul 2021|
- Univerisity of Nottingham
|Supervisor||Liang Xia (Supervisor), Ruibin Bai (Supervisor) & Yupeng Wu (Supervisor)|
- air source heat pump
- thermal performance
- novel absorber