Autocorrelated residuals from regression models of building energy use present problems when attempting to estimate retrofit energy savings and the uncertainty of the savings. This paper discusses the causes of autocorrelation in energy use models and proposes a method to deal with autocorrelation. A hybrid of ordinary least squares (OLS) and autoregressive (AR) models is developed to accurately predict energy use and give reasonable uncertainty estimates. Only linear models are considered because both the data and the physical theory for many commercial buildings support this choice (Kissock, 1993). A procedure for model selection is presented and tested on data from three commercial buildings participating in the Texas LoanSTAR program. In every case examined, the hybrid OLS-AR model provided the best estimate of energy use and the most robust estimate of uncertainty.
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February 1999
Research Papers
Prediction Uncertainty of Linear Building Energy Use Models With Autocorrelated Residuals
D. K. Ruch,
D. K. Ruch
Department of Mathematics, Sam Houston State University, Huntsville, TX
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J. K. Kissock,
J. K. Kissock
Department of Mechanical Engineering, University of Dayton, Dayton, OH
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T. A. Reddy
T. A. Reddy
Department of Civil and Architectural Engineering, Drexel University, Philadelphia, PA
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D. K. Ruch
Department of Mathematics, Sam Houston State University, Huntsville, TX
J. K. Kissock
Department of Mechanical Engineering, University of Dayton, Dayton, OH
T. A. Reddy
Department of Civil and Architectural Engineering, Drexel University, Philadelphia, PA
J. Sol. Energy Eng. Feb 1999, 121(1): 63-68 (6 pages)
Published Online: February 1, 1999
Article history
Received:
June 1, 1998
Revised:
November 1, 1998
Online:
February 14, 2008
Citation
Ruch, D. K., Kissock, J. K., and Reddy, T. A. (February 1, 1999). "Prediction Uncertainty of Linear Building Energy Use Models With Autocorrelated Residuals." ASME. J. Sol. Energy Eng. February 1999; 121(1): 63–68. https://doi.org/10.1115/1.2888144
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