Prediction of cooling energy consumption in building using machine learning techniques

Abstract

The objective of this study is to diagnose and quantify cooling energy consumptions of a typical residential building, Our aim was to increase the energy efficiency of a solar cooling system by utilizing an innovative combination of optimized solar cooling, storage techniques, and absorption chillers with the use of the highly developed machine learning techniques such as the Artificial neural networks. This was done with the intention of meeting as much of the world's energy demand as possible with high renewable energy fractions.