Abstract
This research aimed to develop an effective algorithm to minimize the energy use of vertical transportation in elevators while controlling the number of passengers in the elevator waiting area and the number of passengers in the elevator during rush hour, thus maintaining social distancing to limit the spread of COVID-19. A mobile application and Internet of Things (IoT) devices were used to electronically communicate between the elevator’s control system and the passengers. IoT devices were used to reduce the number of passengers waiting for an elevator and passengers’ waiting time, while the energy consumption of the lift was reduced by using passenger scheduling and elevator stopping strategies. Three mathematical models were formulated to represent the different strategies used to cause the elevator to stop. These strategies were normal (allowing the elevator to stop at every floor), odd–even (some elevators are allowed to stop at odd floors and others are allowed to stop at even floors of the building), and high–low (some elevators are allowed to stop at high floors and others are allowed to stop at low floors of the building). Lingo v.11 and the differential evolution algorithm (DE) were used to address the optimal scheduling of the passengers and the elevators. The computational results show that the odd–even strategy had a 13.91–23.71% lower energy consumption compared with the high–low and normal strategies. Furthermore, the use of DE consumed 6.67–7.99% less energy than the use of Lingo.v11. Finally, the combination of DE and the designed application reduced the number of waiting passengers, the average passenger waiting time, and the total energy consumption by 74.55%, 75.12%, and 45.01%, respectively.
Highlights
We can see that the use of differential evolution algorithm (DE) and the designed application can reduce the number of passengers that have to wait in the elevator waiting area and the average waiting time by 74.55% and 75.12%, respectively, while the energy used was reduced by 45.01%
We developed a mathematical model to represent passenger and elevator scheduling in order to optimize the energy consumption of elevators using the differential evolution algorithm (DE)
An application was designed to communicate between the elevator control system and the passenger in order to manage the waiting time and number of passengers waiting in the elevator’s waiting area, aiming to reduce the spread of COVID-19
Summary
Climate change is the most important problem that currently faces the world. Greenhouse gas (GHG) emissions are the most significant factor in the climate change problem. In a group of six elevators in a high-rise building, the yearly consumption of electricity was around 138,240 kWh, which equals an emission of 67.35 ton CO2eq [5]. Making the energy consumption of elevators in high-rise buildings more efficient will lead to a reduction in GHG emissions and contribute to establishing sustainable cities across the world [6,7,8]. The use of elevators (lifts) in high office buildings generates several problems, which are: (1) the high electricity consumption for the transportation of office workers to their office, and (2) the fact that, during rush hour, office workers must wait and use a lift at the same time.
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