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.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/3900 |
| Date | 16 August 2006 |
| Creators | Shao, Xiaojie |
| Contributors | Claridge, David E. |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Thesis, text |
| Format | 2325273 bytes, electronic, application/pdf, born digital |
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