Study on Energy-saving Control of Large Central Air-conditioning System Based on BAS-PSO

• Published in: Zhìlěng xuébào Vol. 42
• Main Authors: Chen Yang, Yao Ye
• Format: Journal Article
• Language: Chinese; English
• Published: Journal of Refrigeration Magazines Agency Co., Ltd 01.08.2021
• Subjects: beetle antennae search algorithm(BAS); central air-conditioning system; optimal control; particle swarm optimization algorithm(PSO)
• ISSN: 0253-4339
• DOI: 10.3969/j.issn.0253-4339.2021.04.043

There are many air supply terminals in the central air-conditioning system of large-scale public buildings, and the load demand varies greatly. Although the commonly used control methods can meet the terminal load demand, their energy consumption is large. In this study, an optimal control model for the air supply and chilled water system of a central air-conditioning system was established. The energy consumption of the system is considered as the optimization goal, and the hybrid algorithm of beetle antennae search-particle swarm optimization algorithm (BAS-PSO) is used to solve this problem, which not only saves energy but also improves the defects of traditional PSO. Considering the air handling subsystem of a centralized air-conditioning system in a public building in Shanghai as an example, modeling and optimization control solutions were carried out. The results show that the maximum energy saving of BAS-PSO is 252.02 kW, and the energy saving rate is approximately 20% compared with the original control scheme, that is, constant air supply temperature control. The experimental test results show that the optimization algorithm can achieve a 14.6% energy saving rate, saving 153.15 kW of energy, which proves that the optimal control model and optimization algorithm have reliable application prospects.