An Energy-Efficient Elevator Operating System that Considers Sensor Information and Electricity Price Changes in Smart Green Buildings

Abstract

In modern smart buildings, the energy consumption of a building is monitored every time. Smart buildings are also equipped with sensors that can collect various physical data such as temperature, motion, and light. In this paper, we use smart sensor technologies in the design of an efficient elevator operating system (EOS). Specifically, multiple sensor devices are used together to detect elevator passengers’ behavior before they arrive at the elevator door and press the elevator call button. The detected information is then delivered to EOS through building networks and the scheduling system utilizes this information for the efficient control of the elevator cars. Specifically, when the number of passengers becomes large, EOS increases the number of working elevator cars to reduce the waiting time of passengers. In contrast, when the elevator traffic lessens, EOS reduces the number of working elevator cars in order to save the energy consumption. Experimental results with a wide range of configurations show that our EOS outperforms the conventional elevator scheduling system that does not consider sensor information or electricity price changes.