Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/19987
Title: Optimal simplified thermal models of building envelope based on frequency domain regression using genetic algorithm
Authors: Xu, X
Wang, S 
Keywords: Frequency domain regression
Genetic algorithm
Parameter optimization
Simplified thermal model
Issue Date: 2007
Publisher: Elsevier
Source: Energy and buildings, 2007, v. 39, no. 5, p. 525-536 How to cite?
Journal: Energy and buildings 
Abstract: Simple and effective building energy models are essentially needed for many applications, such as building performance diagnosis and optimal control, etc. The energy model involves two important parts of building components, i.e., building envelopes and building internal mass. This paper presents a methodology for parameter optimization of 3R2C thermal network model of building envelopes (composed of three resistances and two capacitances) based on frequency domain regression using genetic algorithm (GA). First, the theoretical frequency characteristics of heat transfer through building envelope are calculated using detailed physical description within the frequency range of concern. Second, the frequency characteristics of the simplified 3R2C model are calculated with random values of individual resistances and capacitances which constrain to total thermal resistance and capacitance. Then, the errors between the theoretical frequency characteristics and the frequency characteristics of the simplified model are calculated. Finally, GA estimator is developed to optimize the parameters of the simplified model, allowing the frequency responses of the simplified model match the actual heat transfer through building envelope the best. Various case studies are conducted also to validate the parameter optimization method of the simplified 3R2C model. The accuracy of simplified models for constructions of different weights is studied.
URI: http://hdl.handle.net/10397/19987
ISSN: 0378-7788
EISSN: 1872-6178
DOI: 10.1016/j.enbuild.2006.06.010
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

44
Last Week
0
Last month
1
Citations as of Aug 17, 2017

WEB OF SCIENCETM
Citations

35
Last Week
0
Last month
1
Citations as of Aug 15, 2017

Page view(s)

42
Last Week
4
Last month
Checked on Aug 21, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.