From Smart to Intelligent: Energy Conservation Management of Air Conditioner System

Hao Yu, Qiuwen Sun, Peiyu Xu and Xiaoxiao Xu ()
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Hao Yu: Nanjing Forestry University
Qiuwen Sun: Nanjing Forestry University
Peiyu Xu: Nanjing Forestry University
Xiaoxiao Xu: Nanjing Forestry University

Chapter Chapter 95 in Proceedings of the 28th International Symposium on Advancement of Construction Management and Real Estate, 2024, pp 1385-1397 from Springer

Abstract: Abstract The construction industry has played a significant role in socio-economic progress while it has brought a large amount of energy consumption during its rapid development. During the whole life cycle of buildings, the energy consumption in operational phase accounts for over 80%, where the electricity consumption of Heating Ventilation and Air Conditioning (HVAC) system takes a large part. Research has been widely carried out on the energy conservation of air conditioner from the perspective of technological innovation and occupant behavior, however, few research focused on such a question during the use of air conditioner in winter: should the air conditioner be turned off from an energy-saving perspective when leaving room for a short time? In order to explore an energy-saving usage mode of air conditioner, this research selected an office as the experimental site and simulated the scenarios of turning off the air conditioner or not for a short leaving. Through five types of experiments and statistical analysis such as Shapiro–Wilk and Mann–Whitney U test, the “balance point” of energy consumption was found. Further, the future intelligent management of energy consumption of HVAC system based on the concept of Agent-based modeling and Digital twin were prospected. The results refuted the popular saying on the Internet and provided guidance for public to objectively understand this issue. A novel concept that combines physical model and data-driven simulation provides a possible solution to improve energy efficiency in buildings.

Keywords: Building; Energy; Field measurement; Simulation; HVAC (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/978-981-97-1949-5_96

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