| This dissertation provides a simple yet powerful approach, the fully layered inverse bin method, to baseline hourly energy use in commercial buildings and illustrates the application through carefully selected case study buildings. The eleven step inverse bin procedure for baselining hourly energy use mainly comprises a simple inverse bin procedure (steps one through seven) and two improvements through the use of thermal lag and humidity sub-binning (steps eight through eleven).; Temperature-based binning for baselining or modeling weather dependent energy use (e.g., heating and cooling energy) and an Hour-of-the-Day binning for weather independent energy use (e.g., electrical energy use) have been developed. This procedure addresses the problem areas suggested by the previous research in the analysis community while keeping the method simple enough to be usable by an HVAC engineer. The inclusion of multiple change points (i.e., bins) through the use of 5°F (3°C) bins enables fitting the non-linear variation of the energy use and hence improves the model's fit significantly over the existing linear and change-point methods. The additional use of humidity sub-binning and lagged temperature as independent variables for sub-binning improves the predictions for latent load dominated building loads or buildings with high thermal mass construction, respectively. |
