Calibrated energy models are useful for commissioning of building systems, measurement and verification (M&V) of retrofits, and prediction of savings due to energy conservation measures (ECMs). Many energy simulation tools exist that are capable of producing calibrated energy models of buildings, but often require professional expertise to reduce user error, resulting in significant monetary and time investments. Automating the calibration process provides a solution to these challenges, by circumventing the need for a professional modeler. Currently, there are no tools capable of automatically calibrating energy models, providing the motivation for this research.
A tool based on MATLAB, Perl, and DOE2 has been developed, utilizing a genetic algorithm (GA) optimization technique to automatically calibrate energy models to utility data. Calibration is achieved through simulation of various building constructions and comparison of energy consumption outputs to utility data. Estimations of unknown building parameters and monthly adjustments to equipment schedules are used to develop a calibrated model. Three buildings serve as test cases for evaluation of the consistency, accuracy, and efficiency of the tool. The GA optimization proves to be less consistent than Particle Swarm Optimization (PSO), however provides similar levels of accuracy at reduced processing times. The resulting models are used as baselines for determining cost effective packages of ECMs through GA optimization. Testing shows ECM evaluation is sensitive to varying building constructions and calibration accuracies, as well as budget constraints and ECM costs.
|Commitee:||Brandemuehl, Michael, Zhai, John|
|School:||University of Colorado at Boulder|
|School Location:||United States -- Colorado|
|Source:||MAI 47/03M, Masters Abstracts International|
|Subjects:||Civil engineering, Energy|
Copyright in each Dissertation and Thesis is retained by the author. All Rights Reserved
The supplemental file or files you are about to download were provided to ProQuest by the author as part of a
dissertation or thesis. The supplemental files are provided "AS IS" without warranty. ProQuest is not responsible for the
content, format or impact on the supplemental file(s) on our system. in some cases, the file type may be unknown or
may be a .exe file. We recommend caution as you open such files.
Copyright of the original materials contained in the supplemental file is retained by the author and your access to the
supplemental files is subject to the ProQuest Terms and Conditions of use.
Depending on the size of the file(s) you are downloading, the system may take some time to download them. Please be