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Description:
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This thesis defines the Energy Balance Load ( BL E ) as the difference between the
heating requirements plus the electric gains in the building and the cooling coil loads . It
then applies a first law energy balance in conjunction with the concepts of analytical
redundancy (AR ) and trend checking to demonstrate that measured values of BL E can be
compared with the simulated characteristic ambient temperature -based BL E to serve as a
useful tool to identify bad data . Uncertainty and sensitivity analysis are introduced to
analyze the impact of each building or system parameter to the simulated values of BL E .
A Visual Basic for Application (VBA ) program has been developed through this research
work , which applies the methodology illustrated in this thesis to automatically prescreen
the measured building energy consumption data with the inputs of several key
parameters . Through case studies of six on -campus buildings , the methodology and the
program successfully identified monitored consumption data that appears to be
erroneous , which may result from incorrect scale factors of the sensors and the
operational changes to the building that may enormously affect the key parameters as the
simulation inputs . Finally , suggestions are given for the on -line diagnostics of sensor
signals . |