Overview of Key Methodologies for Predicting Energy Consumption in Buildings

In recent years, the building sector emerges as a major contributor to global energy consumption, accounting for a significant portion of the world’s overall energy use and plays a leading role in global greenhouse gas emissions. This has raised concerns about the environmental impact and sustainability of current building practices. However, accurately predicting building energy consumption remains a complex and challenging task due to the intricate interactions between various factors such as building design, materials, systems, and occupant behavior. In light of this, the present chapter aims to offer an introductory overview of the contemporary trends in building energy consumption, as well as an in-depth examination of the diverse methodologies and approaches that have been extensively employed by researchers in building energy consumption prediction. A critical analysis of the procedure in implementing energy consumption prediction, the strengths and weaknesses of each approach will be provided, along with a discussion of the key challenges faced by the industry and potential future directions for research and development in the realm of energy-efficient and sustainable buildings. The chapter revealed an exponential increase trend in annual publication in building energy consumption prediction. Artificial intelligence (AI) methods have played predominant role and been extensively applied to tackle a variety of challenges. This chapter will serve as a valuable resource for scholars, practitioners, and policymakers seeking to gain a deeper understanding of the factors influencing building energy consumption and the strategies that can be employed to reduce its environmental footprint.