Machine Learning-Based Building Energy Consumption Prediction

Abstract

Energy is the lifeblood of modern societies. In the past decades, the world's energy consumption and associated CO2 emissions have increased rapidly due to the increases in population and comfort demand of people. In this decade, the increase in energy consumption and associated CO2 emissions are expected to continue due to the demand coming from developing countries such as China, India, and some Middle East countries. Negative environmental impacts, such as air pollution and global warming, are being triggered by the generation and use of non-renewable energy, including oil and natural gas. Buildings are a significant source of the world's energy consumption. The building sector is responsible for 39% and 40% of the energy consumption and 38% and 36% of the CO2 emissions in the U.S. (Becerik-Gerber et al. 2014) and Europe (Ahmad et al. 2014), respectively. Buildings, therefore, offer a great potential for reducing the world's energy consumption and limiting the negative impacts caused by the use of non-...