期刊
AUTOMATION IN CONSTRUCTION
卷 18, 期 3, 页码 302-309出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.autcon.2008.09.003
关键词
Data fusion; Cooling load measurement; Building automation system
资金
- Research Grants Council (RGC) of the Hong Kong SAR [PolyU 5323/08E]
Accurate and reliable building load measurement is essential for robust chiller sequencing control, building air-conditioning system performance monitoring and optimization. This paper presents a scheme adopting the data fusion technique to improve the quality of building cooling load measurement of building automation systems. The strategy uses two types of measurement information on the cooling load. i.e., direct measurement of building cooling load, which is calculated directly using the differential water temperature and water flow rate measurements, and indirect measurement of building cooling load, which is calculated using a model using the instantaneous chiller electrical power input. Capitalizing their own advantages and disadvantages, a data fusion algorithm is developed to merge these two types of data to remove outliers and system errors as well as to reduce the impacts of measurement noises. Meanwhile, a method is implemented to provide quantitative evaluation of the degree of reliability of the merged measurement. Validation of the data fusion algorithm is conducted using field data collected from a chiller plant in a high-rising building in Hong Kong. (C) 2008 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据