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.