暖通空调
热舒适性
空调
改装
建筑工程
高效能源利用
楼宇自动化
室内空气质量
水准点(测量)
模拟
工程类
通风(建筑)
计算机科学
控制工程
气象学
机械工程
环境工程
热力学
结构工程
电气工程
物理
大地测量学
地理
作者
Haifeng Lan,Cynthia Hou,Zhonghua Gou,Man Sing Wong,Zhe Wang
标识
DOI:10.1016/j.buildenv.2023.110592
摘要
To respond to the increasing demand for a comfortable, productive and energy efficient study environment, the application of artificial intelligence technologies in the smart control of Heating, ventilation, and air conditioning (HVAC) systems plays an increasingly important role. This research uses a classroom, equipped with a traditional central HVAC system, in Hong Kong as a case study to demonstrate an innovative approach for a more intelligent and efficient HVAC system. Through a field investigation (i.e. measurement and questionnaire) and Computational Fluid Dynamics (CFD) simulation, it is found that the number and spatial location of students have a significant impact on their thermal comfort. Applying a computer vision model (YOLOv5) detected dynamic occupant information (variations in student numbers and locations) in a classroom, the SimScale (a cloud-native simulation platform) was then used to estimate the current thermal comfort state (predicted mean vote, PMV) and change in PMV (ΔPMV) of students in the classroom. Furthermore, a fuzzy logic control system is implemented to adjust air temperature and air velocity based on the simulation results. Preliminary scenario analysis has proven the feasibility of the proposed smart HVAC system for classrooms, as well as its ability to provide better quality of thermal comfort with more robust control. This study contributes to the smart and low-carbon retrofitting of university buildings with traditional central HVAC systems, while also serving as a benchmark for the energy-efficient transformation of HVAC systems in other types of indoor spaces.
科研通智能强力驱动
Strongly Powered by AbleSci AI