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Evaluation of a case-based Reasoning Energy Prediction Tool for Commercial Buildings
Abstract
This paper presents the results of an energy
predictor that predicts the energy demand of
commercial buildings using Case Based Reasoning
(CBR). The proposed approach is evaluated using
monitored data in a real office building located in
Varennes, Quebec. The energy demand is predicted
at every hour for the following three hours using
weather forecasts. The results show that during
occupancy, 7:00 to 17:00, the coefficient of
variance of the root-mean-square-error (CVRMSE)
is below 12.3%, the normalized mean bias
error (NMBE) is below 1.3% and the root-meansquare-
error (RMSE) is below 16.6 kW. When the
statistical criteria are calculated for all hours of the
day, the CV-RMSE is 13.9%, the NMBE is 2.7%
and the RMSE is 17.9 kW. The case study
demonstrates that CBR can be used for energy
demand prediction and could be implemented in
building operation systems.
Citation
Monfet, D.; Arkhipova, E.; Choiniere, D. (2013). Evaluation of a case-based Reasoning Energy Prediction Tool for Commercial Buildings. Energy Systems Laboratory (http://esl.tamu.edu); Texas A&M University (http://www.tamu.edu). Available electronically from https : / /hdl .handle .net /1969 .1 /151419.