A review of artificial intelligence based building energy prediction with a focus on ensemble prediction models

Building energy usage prediction plays an important role in building energy management and conservation. Building energy prediction contributes significantly in global energy saving as it can help us to evaluate the building energy efficiency; to conduct building commissioning; and detect and diagnose building system faults. AI based methods are popular owing to its ease of use and high level of accuracy. This paper proposes a detailed review of AI based building energy prediction methods particularly, multiple linear regression, Artificial Neural Networks, and Support Vector Regression. In addition to the previously listed methods, this paper will focus on ensemble prediction models used for building energy prediction. Ensemble models improve the prediction accuracy by integrating several prediction models. The principles, applications, advantages, and limitations of these AI based methods are elaborated in this paper. Additionally, future directions of the research on AI based building energy prediction methods are discussed.