AN ESTIMATE OF ENERGY CONSUMPTION FOR HOUSING BUILDINGS IN HOT CLIMATIC ZONES THROUGH ARTIFICAL INTELLIGENCE METHODS: CASE OF ANTALYA

Kübra SÜMER HAYDARASLAN¹ , Ersin HAYDARASLAN²

Buildings use about one-third of total energy consumed in order to meet their heating and cooling needs. The building envelope that enables to protect it from physical factors in the outer environment is quite effective upon the amount of energy consumed. For the energy efficient solutions, it is necessary to enhance the heating and cooling performance of the building envelope. With this aim, in the study, the energy loads were calculated, which were consumed for heating and cooling by a building established as a reference through a simulation program in the province of Antalya, which respects a hot climatic zone, and the shifts in yearly heating and cooling loads of the alternative models were examined, which were developed by changing the thermal insulation thickness and the window-to-wall area ratio. In the study, the modern, effective artificial intelligence methods were used to enhance the energy performance of multi-dimensional buildings. Of the models for which heating and cooling load calculation had not been made before, the estimates for the thermal loads were made using an energy simulation program, and it has been reached that thermal insulation thickness and window-to-wall area ratio have effect on both loads.

Keywords
Thermal Performance, Heating Load, Cooling Load, Thermal Insulation, Artificial Intelligence,