Optimal Control Strategy for Variable Air Volume Air-Conditioning Systems Using Genetic Algorithms

Nam-Chul Seong, Jee-Heon Kim and Wonchang Choi
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Nam-Chul Seong: Eco-System Research Center, Gachon University, Seongnam 13120, Korea
Jee-Heon Kim: Eco-System Research Center, Gachon University, Seongnam 13120, Korea
Wonchang Choi: Department of Architectural Engineering, Gachon University, Seongnam 13120, Korea

Sustainability, 2019, vol. 11, issue 18, 1-12

Abstract: 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.

Keywords: heating, ventilation and air-conditioning (HVAC) system; variable air volume (VAV); optimization; genetic algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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