Sensitivity of the total heat loss coefficient determined by the energy signature approach to different time periods and gained energy

Energy and Buildings

Volumn 41, Issue 7, 2009, Pages 801-808

  Sjogren J U ^a   Andersson, S ^a   Olofsson, T ^a  

^a UMEÅ UNIVERSITY   (Sweden)

Author keywords

Energy performance; Energy signature; Gain factor; Household electricity; Indoor temperature; Total heat loss coefficient

Indexed keywords

ENERGY PERFORMANCE; ENERGY SIGNATURE; GAIN FACTOR; HOUSEHOLD ELECTRICITY; INDOOR TEMPERATURE; TOTAL HEAT LOSS COEFFICIENT;

ATMOSPHERIC TEMPERATURE; BUILDINGS; CASCADES (FLUID MECHANICS); ELECTRICITY; ELECTROMAGNETIC WAVES; ENERGY MANAGEMENT; ENTHALPY; HEAT LOSSES; SOLAR RADIATION; SPACE HEATING; SUN; WATER SUPPLY;

SOLAR ENERGY;

EID: 67349098530     PISSN: 03787788     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.enbuild.2009.03.001     Document Type: Article

References (36)

1. Augenbroe G. Trends in building simulation. Building and Environment 37 (2002) 891-902
2. Madsen H., and Holst J. Estimation of continuous-time models for heat dynamics of a building. Energy and Buildings 22 (1995) 67-79
3. Seem J.E., and Braun J.E. Adaptive methods for real-time forecasting of building electrical demand. ASHRAE Transactions 97 2 (1991) 710-721
4. Anstett M., and Kreider J.F. Applications of neural networking models to predict energy use. ASHRAE Transactions 99 1 (1993) 505-517
5. Kreider J.F., and Haberl J.S. Predicting hourly building energy use: the great energy predictor shoot-out-overview and discussion of results. ASHRAE Transactions 17 7 (1994) 1104-1118
6. Haberl J.S., and Thamilseran S. The great energy predictor shootout. II. Measuring retrofit savings-overview and discussion of results. ASHRAE Transactions 3 4 (1996) 419-435
7. Olofsson T., Andersson S., and Östin R. Energy load predictions for buildings based on a total demand perspective. Energy and Buildings 28 1 (1998) 109-116
8. Olofsson T., Andersson A., and Östin R. A method for predicting the annual building heating demand based on limited performance data. Energy and Buildings 28 1 (1998) 101-108
9. Haberl J.S., and Claridge D.E. An expert system for building energy consumption analysis: prototype results. ASHRAE Transactions 93 1 (1987) 979-998
10. Haberl J.S., and Claridge D.E. An expert system for building energy consumption analysis: applications at a university campus. ASHRAE Transactions 94 1 (1988) 1037-1062
11. Reddy T.A., and Claridge D.E. Using synthetic data to evaluate multiple regression and principal component analyses for statistical modeling of daily building energy consumption. Energy and Buildings 21 (1995) 35-44
12. Ruch D., Lu Chen, Haberl J.S., and Claridge D.E. A change-point principal component analysis (CP/PCA) method for predicting energy usage in commercial buildings: the PCA model. Journal of Solar Energy Engineering 115 (1993) 77-84
13. Olofsson T., and Andersson S. Overall heat loss coefficient and domestic energy gain factor for single-family buildings. Building and Environment 37 11 (2002) 1019-1026
14. Lundin M., Andersson S., and Östin R. Further validation of a method aimed to estimate building performance parameters. Energy and Buildings 37 8 (2005) 867-871
15. Zmeureanu R., and Fazio P. Analysis of the energy performance of office buildings in Montreal in 1988. Energy and Buildings 17 (1991) 63-74
16. Rabl A., and Rialhe R. Energy signature models for commercial buildings: test with measured data and interpretation. Energy and Buildings 10 (1992) 143-154
17. Westergren K.-E., Högberg H., and Norlen U. Monitoring energy consumption in single-family houses. Energy and Buildings 29 3 (1999) 247-257
18. Day A.R., Knight I., Dunn G., and Gaddas R. Improved methods for evaluating base temperature for use in building energy performance lines. Building Services Engineering Research and Technology 24 4 (2003) 211-228
19. Yu F.W., and Chan K.T. Energy signatures for assessing the energy performance of chillers. Energy and Buildings 37 7 (2005) 739-746
20. Ghiaus C. Experimental estimation of building energy performance by robust regression. Energy and Buildings 38 (2006) 582-587
21. Hammarsten S. A critical appraisal of energy-signature models. Applied Energy 26 (1987) 97-110
22. Sonderegger R.C. Baseline model for utility bill analysis using both weather and non-weather-related variables. ASHRAE Transactions 104 2 (1998) 859-870
23. Fels M.F. PRISM: an introduction. Energy and Buildings 9 (1986) 5-18
24. American Society of Heating. Refrigerating and Air-Conditioning Engineers (ASHRAE) (2005), ASHRAE Handbook Fundamentals, Atlanta, USA
25. PROFU Report, Internal Documentation, Mölndal (in Swedish), 2006.
26. Sjögren J.-U., Andersson S., and Olofsson T. An approach to evaluate the energy performance of buildings based on incomplete monthly data. Energy and Buildings 39 (2007) 945-953
27. www.stockholmwater.se.
28. www.umeaenergi.se.
29. Bladh G. Förbrukningsprofiler, ProEco, Internal Documentation Göteborg (2004) (in Swedish)
30. H. Bagge, C. Hiller, J.-U. Sjögren, Hushållsel-Framtidens uppärmning, Bygg & Teknik nr 8, 2006 (in Swedish).
31. www.scb.se.
32. Ellegård K. Den Gränslösa Medborgaren (2002) (in Swedish)
33. C.A. Boman, B.-M. Jonsson, S. Skogberg, Mätning av innetemperatur, Statens institut för byggnadsforskning, ELIB-rapport, 99-1350190-3, 1993, p. 4 (in Swedish).
34. www.equa.se.se.
35. Swedish HVAC Handbook, VVS Tabeller och Diagram Förlags AB VVS AB. (1974) (in Swedish)
36. Bagge H., Nilsson A., and Elmroth A. Effects of passive solar heat on energy use and indoor temperatures in residential buildings. In: Fazio P., et al. (Ed). Research in Building Physics and Building Engineering (2006), Taylor & Francis, London, UK