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冯增喜

硕士生导师
教师姓名:冯增喜
教师拼音名称:fengzengxi
所在单位:建筑设备科学与工程学院
职务:建筑设备科学与工程学院副院长
学历:博士研究生
性别:男
学位:博士学位
职称:副教授
在职信息:在职
主要任职:西安建筑科技大学建科学院专业教师、副院长
其他任职:陕西省自动化学会智能建筑与楼宇自动化专业委员会副秘书长
毕业院校:西安建筑科技大学
所属院系:建筑设备科学与工程学院
学科:控制科学与工程    
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论文成果
Improved Multi-Objective Coati Optimization Algorithm for Optimizing Energy Efficiency and Thermal Comfort in Chilled Water Systems
发布时间:2025-12-20    点击次数:

所属单位:建筑设备科学与工程学院

发表刊物:Journal of Thermal Science and Engineering Applications

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

摘要: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.

第一作者:冯增喜

论文类型:期刊论文

卷号:17(4): 041009

ISSN号:1948-5085

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发表时间:2025-02-21