Development and Application of a Statistical Methodology to Evaluate the Predictive Accuracy of Building Energy Baseline Models:
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Development and Application of a Statistical Methodology to Evaluate the Predictive Accuracy of Building Energy Baseline Models:

Abstract

This  paper  documents  the  development  and  application  of  a  general  statistical  methodology to assess the accuracy of baseline energy models, focusing on its application  to  Measurement  and  Verification  (M&V)  of  whole-­‐building  energy  savings.  The methodology complements the principles addressed in resources such as ASHRAE Guideline  14  and  the  International  Performance  Measurement  and  Verification  Protocol. It requires fitting a baseline model to data from a ``training period’’ and using the  model  to  predict  total  electricity  consumption  during  a  subsequent  ``prediction  period.’’ We  illustrate  the  methodology  by  evaluating  five  baseline  models  using  data  from  29  buildings. The training period and prediction period were varied, and model predictions of  daily,  weekly,  and  monthly  energy  consumption  were  compared  to  meter  data  to  determine model accuracy. Several metrics were used to characterize the accuracy of the predictions, and in some cases the best-­‐performing model as judged by one metric was not the best performer when judged by another metric.

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