Detection and interpretation of anomalies in building energy use through inverse modeling

This article presents a study in which three inverse modeling techniques were applied to hourly heating and cooling load data extracted from 35 office buildings in Ottawa, Canada. These modeling techniques were three-parameter change point models, regression trees, and artificial neural networks. The change point models were trained with outdoor temperature data, whereas the other two models were trained with four regressors: outdoor …