建筑设备科学与工程学院

Journal of Thermal Science and Engineering Applications

chilled water system, indoor thermal comfort, multi-objective coati optimization algorithm, parameter optimization, energy efficiency, energy systems, thermal systems

As the main energy consumption part of the central air-conditioning systems, the energy saving of the chilled water system is particularly crucial. This system realizes heat exchange with indoor air by delivering chilled water to air-conditioning units, effectively regulating indoor temperature and humidity to ensure thermal comfort. In this article, an improved multi-objective coati optimization algorithm (IMOCOA) is used to optimize the operating parameters and thermal comfort environment parameters of chilled water systems to improve thermal comfort and reduce energy consumption. The algorithm introduces chaotic mapping to enhance search diversity, balances global and local search capabilities through Levy flight and Gauss variation strategies, and uses location greedy choices to help coatis jump out of local optima. To verify the optimization effect of IMOCOA, a multi-objective optimization model was established, combining the energy consumption model of the chilled water system and the simplified thermal comfort model. Key parameters, including chilled water supply temperature, pump speed ratio, indoor temperature, and relative humidity, are optimized. The simulation results from the experiments show that the average energy-saving rate of the chilled water system using IMOCOA is 7.8% and thermal comfort is improved by 19.6%. Compared to other optimization algorithms, this method demonstrates a better optimization effect.

fengzengxi

Journal paper

17(4): 041009

1948-5085

no

2025-02-21