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A smart elevator scheduler that considers dynamic changes of energy cost and user traffic
- A smart elevator scheduler that considers dynamic changes of energy cost and user traffic
- Ahn S.; Lee S.; Bahn H.
- Ewha Authors
- 반효경; 이소윤
- SCOPUS Author ID
- 반효경; 이소윤
- Issue Date
- Journal Title
- Integrated Computer-Aided Engineering
- Integrated Computer-Aided Engineering vol. 24, no. 2, pp. 187 - 202
- electricity price; Elevator scheduling; genetic algorithm; group elevator; smart building
- IOS Press
- SCIE; SCOPUS
- Document Type
- With the recent advances in energy-aware building technologies, the electricity usage of a smart building is detected every moment and might have different costs at each time slot of a day. This article presents a new elevator scheduling algorithm for a smart building that considers the dynamic changes of electricity price and passenger traffic. The goal of our algorithm is to minimize the electricity charge without increasing passengers' waiting time. To this end, we use a control parameter to increase the number of working elevator cars when the passenger traffic is heavy or the electricity price becomes low. In contrast, when the electricity price becomes high (i.e., peak time), the system adjusts the control parameter to reduce the number of working elevator cars. This is not a simple issue as the two goals we pursue sometimes conflict. Thus, we use an optimization technique based on genetic algorithms in the design of our scheduler. To evaluate the proposed elevator scheduling system, we conduct experiments under synthetic and realistic workload conditions. The results show that the proposed elevator scheduling system significantly saves the electricity charge of the conventional elevator scheduling system. Specifically, the average reduction in the electricity charge is 68.3% without sacrificing passengers' waiting time. © 2017 - IOS Press and the author(s).
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- 엘텍공과대학 > 컴퓨터공학과 > Journal papers
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