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P2-2. Equipment Scheduling
and Cycling > Background
Detailed electrical-load information, at
the component or
system level, is not routinely
measured because
of the cost of obtaining
and analyzing the
data. Much has been learned from utility-sponsored
building surveys
where submeters were installed. But due to the expense of installing submeters,
the benefits of such
programs have been limited
to building-class
level information rather
than insights into
the operation of many
individual buildings. For load information to be cost-effective
for load management
and diagnostics, less
expensive and more
capable instrumentation
is needed.
Electrical-power data are useful for both
whole-building performance
assessments and
component-specific
Fault Detection and Diagnostics
(FDD). Over a period of 16 years, MIT has developed
a series of electrical
load monitors that
are capable, to varying
degrees of accuracy,
of identifying which
pieces of equipment
in the connected
load are operating, and
providing specific
information about their
power use and electrical
characteristics. These meters are known as Non-intrusive Load
Monitors (NILMs).
The NILM is sensitive to
the change in total
power at the time equipment
turns on or off. If power can be accurately estimated at this
time and if there
are reasonable models for
equipment energy
use between the time of
startup and shutdown,
it is possible to accurately
estimate equipment
energy consumption. In addition, the measurement and analysis
of power at startup
and shutdown provides
a powerful tool for
detecting a large class
of faults in motor-driven
equipment. This project focused on fully automated analysis
of electrical data
for detecting equipment
scheduling and cycling
faults.
At the beginning of this project, the on-line
NILM was capable of detecting loads via analysis
of the electrical-power transients observed
during start-up of equipment. All other analysis,
notably detection of loads via changes in
steady-state power and detection of faults,
was done off-line, via a combination of algorithms
and intervention of an analyst.
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