Utilization of least squares support vector machine for predicting the yearly exergy yield of a hybrid renewable energy system composed of a building integrated photovoltaic thermal system and an earth air heat exchanger system

In the present research, the least squares support vector machine technique is employed to develop a relationship to predict the total useful exergy yield of a hybrid renewable energy system consisting of a building integrated photovoltaic thermal (PVT) system and an earth air heat exchanger (EAHX) system. This system is designed to bring the temperature of the ambient air to the desired temperature and also to supply the required electricity of the building. In the cold months of the year, the ambient air is preheated by passing through the PVT and EAHX systems. In the hot months of the year, the ambient air is pre-cooled by passing through the EAHX system, while the air leaving the building is also used to cool the photovoltaic panels. The electricity produced by photovoltaic panels is used throughout the year to meet the electricity needs of the building. The dimensions of different parts of the PVT and EAHE systems along with air flow rate are considered as the main variables and the annual exergy yield of the hybrid system is considered as the dependent variable. The LSSVM model in terms of (R = 0.9670, RMSE=1,152,165.21, and MAPE=29,264.80) resulted in promising outcomes to simulate the useful exergy.