A baselining methodology is crucial to verify savings from energy conservation programs, to determine progress toward preset energy-efficiency goals, and to implement performance-based shared energy savings contracts. This paper discusses the various issues involved and structures a formal baselining methodology at the facility level or whole-building level when monthly utility bills are available. Normalizing annual energy use for changes in the conditioned area and in the number of occupants as well as correcting for increases in the connected load (a phenomenon referred to as 'creep') are also discussed. The various functional forms assumed by the regression models with outdoor dry-bulb temperature as the only regressor variable are described in the framework of two widely used energy modeling software packages. An important aspect of this paper is the development of prediction uncertainty bands for the regression model, both at the monthly level and at the annual level, an issue of key importance if one wishes to reach statistically meaningful conclusions regarding month-to-month and year-to-year changes in observed energy use with respect to the baseline year. Finally, a statistical method is described by which one can overcome model identification limitations in case the read dates of the utility bills are not known. A companion paper presents the results of applying this baselining methodology to eight Army installations nationwide.
|Original language||English (US)|
|Title of host publication||ASHRAE Transactions|
|Number of pages||12|
|State||Published - 1997|
ASJC Scopus subject areas
- Fluid Flow and Transfer Processes