The measured energy savings from retrofits
in buildings is often determined as the difference
between the energy consumption predicted by a
baseline model and the measured energy
consumption during the post retrofit period.
Most baseline models are developed either by
regressing the daily energy consumption versus
the daily average temperature ( daily model ) or
by regressing the monthly energy consumption
versus the monthly average temperature (
monthly model ).
Savings measurement for buildings such as
primary and secondary schools (k-12 school) is
very difficult due to the special operating
schedules of such buildings. Currently, savings
are either determined by simple pre-post utility
bill comparison or by a method where by the
baseline model consists of two separate models:
a 3-P model for non-summer months, and a
mean model for the summer months.
(Landman, 1996).
This paper proposes an improved
methodology for identifying baseline models of
energy use from utility billing data for buildings
such as schools which have important daily and
seasonal variations in occupancy. By explicitly
considering the occupancy rate in the model, we
are able to generalize it and retain the distinction
between energy use levels during occupied and
unoccupied days of the year. Thus the modified
baseline model accounts, not only for the effect
of weather, but also for the influence of school
schedules. The proposed methodology has been
evaluated against the previous 3-P-mean proposed by Landman for 10 schools in Texas
for which several years
of monitored data are available. Incorporation of
scheduling information reduced the average CV
of the model from 23.6% using Landman's
method to 10.9% using our proposed method