期刊
SUSTAINABILITY
卷 11, 期 18, 页码 -出版社
MDPI
DOI: 10.3390/su11185122
关键词
heating; ventilation and air-conditioning (HVAC) system; variable air volume (VAV); optimization; genetic algorithm
资金
- Korea Agency for Infrastructure Technology Advancement (KAIA) - Ministry of Land, Infrastructure and Transport [19AUDP-B099702-05]
- Korea Agency for Infrastructure Technology Advancement (KAIA) [99690] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
This study is aimed at developing a real-time optimal control strategy for variable air volume (VAV) air-conditioning in a heating, ventilation, and air-conditioning (HVAC) system using genetic algorithms and a simulated large-scale office building. The two selected control variables are the settings for the supply air temperature and the duct static pressure to provide optimal control for the VAV air-conditioning system. Genetic algorithms were employed to calculate the optimal control settings for each control variable. The proposed optimal control conditions were evaluated according to the total energy consumption of the HVAC system based on its component parts (fan, chiller, and cold-water pump). The results confirm that the supply air temperature and duct static pressure change according to the cooling load of the simulated building. Using the proposed optimal control variables, the total energy consumption of the building was reduced up to 5.72% compared to under 'normal' settings and conditions.
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