  It is envisioned that building systems will become active participants in the
smart grid operation by controlling their energy consumption to optimize
complex criteria beyond ensuring local end-use comfort satisfaction. A forecast
of the building energy consumption will be necessary to enable integration
between building and grid operation. Such forecast will be affected by
parametric and measurement uncertainty. In this paper we develop a methodology
for quantifying the sensitivity of optimal hourly energy consumption forecasts
to various sources model and measurement uncertainty. We demonstrate the
approach for a building heating ventilation and air conditioning (HVAC) system
use-case.
