Evaluation of the Predictive Accuracy of Five Whole Building Baseline Models
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
This report documents the relative and absolute performance of five baseline models used to characterize wholebuilding energy consumption. The Pulse Adaptive Model1, multi-parameter change-point, mean-week, day-time-emperature, and LBNL models were evaluated according to a number of statistical ‘goodness of fit’ metrics, to determine their accuracy in characterizing the energy consumption of a set of 29 buildings. The baseline training period, prediction horizon, and predicted energy quantity (daily, weekly, and monthly energy consumption) were varied, and model predictions were compared to interval meter data to determine the accuracy of each model. Three combinations of baseline training periods and prediction horizons were considered: 6 months of training to generate a 12-month prediction; 9 months of training to generate a 7-month prediction; and 12 months of training to generate a 6- month prediction.
- Research Organization:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC)
- DOE Contract Number:
- AC02-05CH11231
- OSTI ID:
- 1172955
- Report Number(s):
- LBNL-5886E
- Country of Publication:
- United States
- Language:
- English
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