Energy Saving in Building Air-Conditioning Systems Based on Hippopotamus Optimization Algorithm for Optimizing Cooling Water Temperature

Yiyang Zheng (), Yaping Gao and Jianwen Gao
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Yiyang Zheng: Beijing Key Lab of Heating, Gas Supply, Ventilating and Air Conditioning Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
Yaping Gao: School of Architecture and Urban Planning, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
Jianwen Gao: Infrastructure Construction Department, China Agricultural University, Beijing 100107, China

Energies, 2025, vol. 18, issue 10, 1-19

Abstract: When traditional HVAC (heating, ventilation, and air-conditioning) systems are in operation, they often run according to the designed operating conditions. In fact, they operate under part-load conditions for more than 90% of the time, resulting in energy waste. Therefore, studying the optimization and regulation of their operating conditions during operation is necessary. Given that the control set point for cooling tower outlet water temperature differentially impacts chiller and cooling tower energy consumption during system operation, optimization of this parameter becomes essential. Therefore, this study focuses on optimizing the cooling tower outlet water temperature control point in central air-conditioning systems. We propose the Hippopotamus Optimization Algorithm (HOA), a novel population-based approach, to optimize cooling tower outlet water temperature control points for energy consumption minimization. This optimization is achieved through a coupled computational methodology integrating building envelope dynamics with central air-conditioning system performance. The energy consumption of the cooling tower was analyzed for varying outlet water temperature set points, and the differences between three control strategies were compared. The results showed that the HOA strategy successfully identifies an optimized control set point, achieving the lowest combined energy consumption for both the chiller and cooling tower. The performance of HOA is better compared to other algorithms in the optimization process. The optimized fitness value is minimal, and the function converges after five iterations and completes the optimization in a single time step when run in MATLAB in only 1.96 s. Compared to conventional non-optimized operating conditions, the HOA strategy yields significant energy savings: peak daily savings reach 4.5%, with an average total daily energy reduction of 3.2%. In conclusion, this paper takes full account of the mutual coupling between the building and the air-conditioning system, providing a feasible method for the simulation and optimization of the building air-conditioning system.

Keywords: cooling tower outlet water temperature; operating energy consumption; central air-conditioning system; hippopotamus optimization algorithm; user-side model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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