Statistical modeling of the building energy balance variable for screening of metered energy use in large commercial buildings

Energy and Buildings

Volumn 77, Issue , 2014, Pages 292-303

  Masuda, Hiroko ^a   Claridge, David E ^a  

^a Texas AandM University   (United States)

Author keywords

Commercial buildings; Data quality; Energy analysis; Energy metering; M V; Regression analysis

Indexed keywords

ATMOSPHERIC TEMPERATURE; ENERGY BALANCE; ENERGY EFFICIENCY; LINEAR REGRESSION; OFFICE BUILDINGS; REGRESSION ANALYSIS;

BUILDING ENERGY PERFORMANCE; BUILDING ENERGY SIMULATIONS; COMMERCIAL BUILDING; DATA QUALITY; ENERGY ANALYSIS; ENERGY METERING; MULTIPLE LINEAR REGRESSION MODELS; OUTSIDE-AIR TEMPERATURE;

INVESTMENTS;

EID: 84898955375     PISSN: 03787788     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.enbuild.2014.03.070     Document Type: Article

References (44)

1. E. Mills, S. Kromer, G. Weiss, and P.A. Mathew From volatility to value: analysing and managing financial and performance risk in energy savings projects Energy Policy 34 2 2006 188 199 (Pubitemid 41283433)
2. U.S. Department of Energy International Performance Measurement and Verification Protocol (IPMVP), vol. DOE/EE-0157 1997 United States Department of Energy Washington, DC
3. ASHRAE Guideline 14-2002: Measurement of Energy and Demand Savings 2002 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. Atlanta, GA
4. American Society of Heating, Refrigerating and Air-Conditioning Engineers Chapter 19, Energy Estimating and Modeling Methods, 2013 ASHRAE Handbook - Fundamentals (I-P Edition) 2013 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. Atlanta, GA 19.1 19.42
5. X. Shao, and D.E. Claridge Use of first law energy balance as a screening tool for building energy data. Part I: Methodology ASHRAE Transactions 112 Pt. 2 2006 717 731 (Pubitemid 44620282)
6. X. Shao First Law Energy Balance as a Data Screening Tool (Master's thesis) 2006 Texas A&M University
7. ASHRAE Guideline 2-2010: Measurement of Energy and Demand Savings 2010 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. Atlanta, GA
8. J.C. Baltazar, Y. Sakurai, H. Masuda, D. Feinauer, J. Liu, J. Ji, D.E. Claridge, S. Deng, and H. Bruner Experiences on the implementation of the 'energy balance' methodology as a data quality control tool: application to the building energy consumption of a large university campus The Seventh International Conference for Enhanced Building Operations, Energy Systems Laboratory San Francisco, CA 2007
9. J.C. Baltazar, D.E. Claridge, J. Ji, H. Masuda, and S. Deng Use of first law energy balance as a screening tool for building energy data: Part II - Experiences of its implementation as a data quality control tool ASHRAE Transactions 118 2012 167 174
10. R.C. Sonderegger Diagnostic tests determining the thermal response of a house ASHRAE Transactions 1 1978 691 702
11. A. Rabl, and A. Rialher Energy signature models for commercial buildings - test with measured data and interpretation Energy and Buildings 19 2 1992 143 154 (Pubitemid 23619889)
12. A. Rabl Parameter estimation in buildings: Methods for dynamic analysis of measured energy use Journal of Solar Energy Engineering - Transactions of the ASME 110 1998 52 66
13. T.A. Reddy, S. Deng, and D.E. Claridge Development of an inverse method to estimate overall building and ventilation parameters of large commercial buildings Journal of Solar Energy Engineering 121 1999 40 46
14. J.U. Sjögren, S. Andersson, and T. Olofsson Sensitivity of the total heat loss coefficient determined by the energy signature approach to different time periods and gained energy Energy and Buildings 41 7 2009 801 808
15. S. Danov, J. Carbonell, J. Cipriano, and J. MartA - Herrero Approaches to evaluate building energy performance from daily consumption data considering dynamic and solar gain effects Energy and Buildings 57 2013 110 118
16. S. Hammarsten A critical appraisal of energy-signature models Applied Energy 26 2 1987 97 110
17. J.U. Sjögren, S. Andersson, and T. Olofsson An approach to evaluate the energy performance of buildings based on incomplete monthly data Energy and Buildings 39 8 2007 945 953 (Pubitemid 46771040)
18. F. Liu, H. Jiang, Y.M. Lee, J. Snowdon, and M. Bobker Statistical Modeling for Anomaly Detection, Forecasting and Root Cause Analysis of Energy Consumption for a Portfolio of Buildings, Tech. Rep. RC25165(W1106-008) 2011 IBM Research Division Thomas J. Watson Research Center, Building Performance Lab, CUNY Institute for Urban Systems
19. H. Reichmuth, and T. Egnor X-view™. The Reichmuth framework II 2013 IEEE Conference on Technologies for Sustainability (SusTech) August 1-2 2013 258 261
20. H. Masuda, and D.E. Claridge Estimation of building parameters using simplified energy balance model and metered whole building energy use Proceedings of the Twelfth International Conference for Enhanced Building Operations, Energy Systems Laboratory Manchester, UK, October 24-25 2012
21. S.J. Emmerich, A.K. Persily, and T.P. McDowell Impact of Infiltration on Heating and Cooling Loads in U.S. Office Buildings, Tech. Rep., Building and Fire Research Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA 2005 TESS, Inc. Madison, WI, USA
22. 2009 International Energy Conservation Code 2009 International Code Council, Inc.
23. F. Flouquet Local weather correlations and bias in building parameter estimates from energy-signature models Energy and Buildings 19 2 1992 113 123 (Pubitemid 23619892)
24. S. Katipamula, T.A. Reddy, and D.E. Claridge Multivariate regression modeling Journal of Solar Energy Engineering 120 3 1998 177 184 (Pubitemid 128735691)
25. B. Abushakra, A. Sreshthaputra, J.S. Haberl, and D.E. Claridge Compilation of Diversity Factors and Schedules for Energy and Cooling Load Calculations, Tech. Rep. ASHRAE RP-1093 2000
26. National Climatic Data Center Quality Controlled Local Climatological Data (2.5.4) 2013 http://cdo.ncdc.noaa.gov/qclcd/QCLCD
27. J.C. Baltazar, J. Haberl, and Y. Sun Solar Test Bench Database 2013 Energy Systems Laboratory, Texas A&M Engineering Experiment Station http://165.91.141.95:6785/
28. J. Cohen, and P. Cohen Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences 2nd ed. 2003 L. Erlbaum Associates Mahwah, N.J
29. S. Kim ppcor: Partial and Semi-partial (Part) Correlation, R Package Version 1.0 2012 http://CRAN.R-project.org/package=ppcor
30. D.W. Schrock, and D.E. Claridge Predicting energy usage in a supermarket Proceedings of the Sixth Symposium on Improving Building Systems in Hot and Humid Climates Dallas, TX, October 3-4 1989 F-19 F-27
31. D. Ruch, and D.E. Claridge A four-parameter change-point model for predicting energy consumption in commercial buildings Journal of Solar Energy Engineering 114 2 1992 77 83
32. J.K. Kissock, T.A. Reddy, and D.E. Claridge Ambient temperature regression analysis for estimating retrofit savings in commercial buildings ASME Journal of Solar Energy Engineering 120 1998 168 176 (Pubitemid 128735690)
33. T.A. Reddy, S. Deng, and D.E. Claridge Development of an inverse method to estimate overall building and ventilation parameters of large commercial buildings Journal of Solar Energy Engineering 121 1999 40 46
34. J.K. Kissock, J.S. Haberl, and D.E. Claridge Development of a Toolkit for Calculating Linear, Change-point Linear and Multiple-linear Inverse Building Energy Analysis Models, Tech. Rep. ASHRAE RP-1050 2004
35. J. Fox Applied Regression Analysis and Generalized Linear Models 2008 Sage Los Angeles
36. H. Masuda, J. Ji, J.C. Baltazar, and D.E. Claridge Use of first law energy balance as a screening tool for building energy use data: experiences on the inclusion of outside air enthalpy variable Proceedings of the Ninth International Conference for Enhanced Building Operations, Energy Systems Laboratory Austin, TX, November 17-19 2009
37. H. Masuda, J.C. Baltazar, J. Ji, and D.E. Claridge Development of data quality control limits for data screening through the "energy balance" method Proceedings of the Sixteenth Symposium on Improving Building Systems in Hot and Humid Climates, Energy Systems Laboratory Plano, TX, December 15-17 2008
38. D. Montgomery, E. Peck, and G. Vining Introduction to Linear Regression Analysis 5th ed. 2012 Wiley Hoboken, NJ
39. C.T. Haan Statistical Methods in Hydrology 2nd ed. 2002 John Wiley & Sons
40. D.K. Ruch, J.K. Kissock, and T.A. Reddy Prediction uncertainty of linear building energy use models with autocorrelated residuals Journal of Solar Energy Engineering 121 1 1999 63 68
41. T.A. Reddy, J.K. Kissock, and D.K. Ruch Uncertainty in baseline regression modeling and in determination of retrofit savings Journal of Solar Energy Engineering 120 1998 185 192 (Pubitemid 128735692)
42. R Core Team R: A Language and Environment for Statistical Computing 2013 R Foundation for Statistical Computing Vienna, Austria http://www.R-project.org/
43. S. Katipamula, T.A. Reddy, and D.E. Claridge Development and application of regression models to predict cooling energy consumption in large commercial buildings The 1994 ASME/JSME/JSES International Solar Energy Conference, ASME San Francisco, CA, March 27-30 1994 307 322
44. T.A. Reddy, S. Katipamula, J.K. Kissock, and D.E. Claridge The functional basis of steady-state thermal energy use in air-side hvac equipment Journal of Solar Energy Engineering 117 1 1995 31 39