Accurate prediction of hourly energy consumption in a residential building based on the occupancy rate using machine learning approaches

• Main Authors: Truong, Le Hoai My, Chow, Ka Ho Karl, Luevisadpaibul, Rungsimun, Thirunavukkarasu, Gokul Sidarth, Seyedmahmoudian, Mehdi, Horan, Ben, Mekhilef, Saad, Stojcevski, Alex
• Format: Article
• Published: MDPI 2021
• Subjects: QC Physics; QD Chemistry; TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.um.edu.my/33947/

In this paper, a novel deep neural network-based energy prediction algorithm for accurately forecasting the day-ahead hourly energy consumption profile of a residential building considering occupancy rate is proposed. Accurate estimation of residential load profiles helps energy providers and utilit...