An automatic energy saving strategy for a water dispenser based on user behavior |
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| Affiliation: | 1. Taiwan Building Technology Center, National Taiwan University of Science and Technology, Taipei, Taiwan;2. Department of Industrial Management, National Taiwan University of Science and Technology, Taipei, Taiwan;3. Department of Electronic and Computer Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan;4. Department of Logistics Engineering, Universitas Pertamina, Jakarta, Indonesia;1. State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha 410082, PR China;2. Laboratory of Science and Technology on Integrated Logistics Support, National University of Defense Technology, Changsha 410082, PR China;1. National Engineering Research Center for Advanced Rolling and Intelligent Manufacturing, University of Science and Technology Beijing, Beijing 100083, China;2. Department of Electronics and Electrical Engineering, Liverpool John Moores University, Liverpool L3 3AF, U.K;3. The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;1. State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, China;2. Department of Building and Real Estate, The Hong Kong Polytechnic University, Hong Kong, China;3. Department of Construction Management, University of Houston, Houston, TX 77204, USA;1. Dept. of Civil, Environmental and Ocean Engineering, Stevens Institute of Technology, 1 Castle Point Terrace, Hoboken, NJ 07030, United States;2. Dept. of Civil and Environmental Engineering, Univ. of Illinois at Urbana-Champaign, 205 N. Mathews Ave., Urbana, IL 61801, United States |
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| Abstract: | Nowadays, numerous public buildings provide water dispensers to supply drinking water which causes more energy consumption. A typical water dispenser periodically heats and cools the water to ensure that hot, warm, and cold water are always available for the user. However, this mechanism is inefficient because the users do not request hot and cool water continuously. Ideally, the boiling and cooling schedule should follow the demand pattern to save electricity consumption. When no demand, a water dispenser can enter a sleep mode.Therefore, this study presents an automatic energy-saving strategy for a water dispenser based on user behavior. The proposed system allows the water dispenser to automatically determine the appropriate time to heat, boil, and enter sleep mode based on user behavior. The proposed control strategy involves several steps. First, it collects historical data, analyzes water consumption behavior. The sensors installed in the water dispenser collect water consumption data. Second, this study applies Recurrent Neural Networks with Long-Short Term Memory to predict future water consumption. Finally, the proposed system utilizes the prediction result to determine heating, cooling, and sleep mode schedule.This study uses a water dispenser on a university campus as a prototype to test the proposed system. The effectiveness of the proposed system is measured by two factors, namely electricity consumption, and customer satisfaction. These two parameters are chosen because the proposed system should reduce electricity consumption while maintaining hot and cold water availability whenever needed. According to the simulation results, the proposed controlling strategy can reduce electricity consumption up to 28% monthly while maintaining a service level of 97%. This result shows that the proposed system is a good control system for water dispensers. By applying this controlling system, public buildings could reduce their energy bills without sacrificing their provision of drinking water. |
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| Keywords: | Water dispenser Water consumption prediction Feature selection Recurrent neural network Energy conservation |
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