Chen, JieKhatib, Akram GhassanGoodman, DavidRazban, Ali2015-02-242015-02-242014https://hdl.handle.net/1805/5943http://dx.doi.org/10.7912/C2/2668Indiana University-Purdue University Indianapolis (IUPUI)Heating, ventilation, and air conditioning (HVAC) is the technology responsible to maintain temperature levels and air quality in buildings to certain standards. In a commercial setting, HVAC systems accounted for more than 50% of the total energy cost of the building in 2013 [13]. New control methods are always being worked on to improve the effectiveness and efficiency of the system. These control systems include model predictive control (MPC), evolutionary algorithm (EA), evolutionary programming (EP), and proportional-integral-derivative (PID) controllers. Such control tools are used on new HVAC system to ensure the ultimate efficiency and ensure the comfort of occupants. However, there is a need for a system that can monitor the energy performance of the HVAC system and ensure that it is operating in its optimal operation and controlled as expected. In this thesis, an air handling unit (AHU) of an HVAC system was modeled to analyze its performance using real data collected from an operating AHU using a wireless monitoring system. The purpose was to monitor the AHU's performance, analyze its key parameters to identify flaws, and evaluate the energy waste. This system will provide the maintenance personnel to key information to them to act for increasing energy efficiency. The mechanical model was experimentally validated first. Them a baseline operating condition was established. Finally, the system under extreme weather conditions was evaluated. The AHU's subsystem performance, the energy consumption and the potential wastes were monitored and quantified. The developed system was able to constantly monitor the system and report to the maintenance personnel the information they need. I can be used to identify energy savings opportunities due to controls malfunction. Implementation of this system will provide the system's key performance indicators, offer feedback for adjustment of control strategies, and identify the potential savings. To further verify the capabilities of the model, a case study was performed on an air handling unit on campus for a three month monitoring period. According to the mechanical model, a total of 63,455 kWh can be potentially saved on the unit by adjusting controls. In addition the mechanical model was able to identify other energy savings opportunities due to set point changes that may result in a total of 77,141 kWh.en-USCC0 1.0 UniversalHVAC AHU EnergyHeating -- Control -- Research -- MethodologyVentilation -- Control -- Research -- MethodologyAir conditioning -- Control -- Research -- MethodologyAir conditioning -- EfficiencyAutomatic controlPredictive controlReal-time controlEvolutionary programming (Computer science)Evolutionary computationSensor networks -- ResearchMATLABEngineering mathematics -- Data processingProcess control -- Data processingPID controllers -- Computer simulationPredictive control -- Computer simulationSustainable engineeringHeating and ventilation industry -- Energy consumptionThesis