Advances in Constructional Engineering

Today, smart buildings are thriving, and elevators, as the core vertical transportation components, have garnered significant attention for their energy consumption issues. This study focuses on energy-saving scheduling algorithms for elevator cluster control systems, delving into the shortcomings of traditional algorithms in energy management and passenger flow adaptation. It innovatively introduces dynamic time regularization and fuzzy logic techniques to collaboratively optimize elevator operations. Through simulation of various building scenarios and on-site testing, the new algorithm accurately balances waiting times and elevator riding experiences, significantly reducing energy consumption and effectively advancing intelligent building elevators to a new stage of high efficiency and energy savings.

Intelligent building; Elevator group control; Energy saving scheduling; Dynamic time regulation; Fuzzy logic