A methodology for identifying and improving occupant behavior in residential buildings

Energy

Volumn 36, Issue 11, 2011, Pages 6596-6608

  Yu Zhun Jerry, Z J ^a   Haghighat, Fariborz ^a   Fung, Benjamin C M ^b   Morofsky, Edward ^c   Yoshino, Hiroshi ^d  

^a Gina Cody School of Engineering and Computer Science   (Canada)

^b Public Works and Government Services Canada ^*  (Canada)

^c Public Works and Government Services Canada   (Canada)

^d TOHOKU UNIVERSITY   (Japan)

Author keywords

Building energy consumption; Data mining; Evaluation; Identification; Occupant behavior

Indexed keywords

ASSOCIATION RULES; BUILDINGS; CLUSTER ANALYSIS; DATA MINING; DOMESTIC APPLIANCES; ENERGY UTILIZATION;

ASSOCIATION RULES MINING; BUILDING ENERGY CONSUMPTION; CLASSIFICATION ANALYSIS; DATA MINING TECHNIQUES; END-USES; ENERGY SAVING POTENTIAL; EVALUATION; OCCUPANT BEHAVIOR; RESIDENTIAL BUILDING; USER ACTIVITY;

ENERGY CONSERVATION;

BUILDING; CLUSTER ANALYSIS; DATA MINING; ENERGY CONSERVATION; ENERGY EFFICIENCY; HOUSEHOLD ENERGY; IDENTIFICATION METHOD; METHODOLOGY;

EID: 80655127634     PISSN: 03605442     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.energy.2011.09.002     Document Type: Article

References (21)

1. Swan L.G., Ugursal V.I. Modeling of end-use energy consumption in the residential sector: a review of modeling techniques. Renewable and Sustainable Energy Reviews 2009, 13(8):1819-1835.
2. Chen S.Q., Li N.P., Guan J., Xie Y.Q., Sun F.M., Ni J. A statistical method to investigate national energy consumption in the residential building sector of China. Energy and Buildings 2008, 40(4):654-665.
3. Tanatvanit S., Limmeechokchai B., Chungpaibulpatana S. Sustainable energy development strategies: implications of energy demand management and renewable energy in Thailand. Renewable and Sustainable Energy Reviews 2003, 7(5):367-395.
4. Ruijven B.V., Vries B.D., Van Vuuren D.P., Van der Sluijs J.P. A global model for residential energy use: uncertainty in calibration to regional data. Energy 2010, 35(1):269-282.
5. Shimoda Y., Asahi T., Taniguchi A., Mizuno M. Evaluation of city-scale impact of residential energy conservation measures using the detailed end-use simulation model. Energy 2007, 32(9):1617-1633.
6. Kenisarin M., Kenisarina K. Energy saving potential in the residential sector of Uzbekistan. Energy 2007, 32(8):1319-1325.
7. Yu Z., Fung B.C.M., Haghighat F., Yoshino H., Morofsky E. A systematic procedure to study the influence of occupant behavior on building energy consumption. Energy and Buildings 2011, 43(6):1409-1417.
8. Ouyang J.L., Hokao K. Energy-saving potential by improving occupants' behavior in urban residential sector in Hangzhou City, China. Energy and Buildings 2009, 41(7):711-720.
9. Al-Mumin A., Khattab O., Sridhar G. Occupants' behavior and activity patterns influencing the energy consumption in the Kuwaiti residences. Energy and Buildings 2003, 35(6):549-559.
10. Zmeureanu R., Fazio P., DePani S., Calla R. Development of an energy rating system for existing houses. Energy and Buildings 1999, 29(2):107-119.
11. Han J.W., Kamber M. Data mining concepts and techniques 2006, Elsevier Inc., San Francisco. 2nd ed.
12. Yu Z., Haghighat F., Fung B.C.M., Yoshino H. A decision tree method for building energy demand modeling. Energy and Buildings 2010, 42(10):1637-1646.
13. Rapid-I - RapidMiner. http://rapid-i.com/content/view/181/190/.
14. Davies D.L., Bouldin D.W. A cluster separation measure. IEEE Transactions on Pattern Analysis and Machine Intelligence 1979, 1:224-227.
15. Quinlan J.R. Induction of decision trees. Machine Learning 1986, 1:81-106.
16. Breiman L., Friedman J.H., Olshen R.A., Stone C.J. Classification and regression trees 1984, Wadsworth Inc., Belmont. 2nd ed.
17. Quinlan J.R. C4.5 Programs for machine learning 1993, Morgan Kaufmann, San Mateo. 1st ed.
18. Association rule mining with WEKA. http://maya.cs.depaul.edu/%7EClasses/Ect584/Weka/associate.html.
19. Murakami S., Akabayashi S., Inoue T., Yoshino H., Hasegawa K., Yuasa K., et al. Energy consumption for residential buildings in Japan 2006, Architectural Institute of Japan, Maruzen Corp. http://tkkankyo.eng.niigata-u.ac.jp/HP/HP/database/index.htm.
20. Helsel D.R., Hirsch R.M. Statistical methods in water resources 2002, U.S. Department of the Interior.
21. Standby Power. Frequently asked questions (FAQs). http://standby.lbl.gov/faq.html.