Impact of Component Uncertainty and Control Loop on Performance in HVAC Systems with Advanced Sequences of Operation
Open Access
- Author:
- Abdel Haleem, Shadi
- Graduate Program:
- Architectural Engineering
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- March 05, 2020
- Committee Members:
- William P Bahnfleth, Dissertation Advisor/Co-Advisor
William P Bahnfleth, Committee Chair/Co-Chair
Donghyun Rim, Committee Member
James Freihaut, Committee Member
Ute Poerschke, Outside Member
Gregory Scott Pavlak, Dissertation Advisor/Co-Advisor
Gregory Scott Pavlak, Committee Chair/Co-Chair
Somayeh Asadi, Program Head/Chair - Keywords:
- Uncertainty quantification
Modelica Buildings Library
Bootstrap
Advanced Sequences
Monte-Carlo
ASHRAE Guideline 36
control sequences
multiple zone VAV
sensitivity analysis
uncertainty analysis
control loop performance assessment (CLPA)
Harris index
Modelica simulation - Abstract:
- This dissertation starts by developing a model-based testbed for a building heating, ventilation, and air-conditioning (HVAC) system that realistically represents the control system operation, then presents a series of studies structured to evaluate advanced control sequences of operation performance on multiple levels: 1) uncertainty quantification that focuses on the sensors and actuators, the interface between the control sequence and the physical system, and 2) control loop performance assessment on the individual loop level and its influence on system-level performance. As advanced control sequences are developed to improve operational efficiency of buildings, it is important to better understand the implications of uncertainty on system design and specification, and its propagation through system components to various performance measures. This dissertation starts by describing the detailed development of a testbed for performing uncertainty quantification in building HVAC system operational parameters, that includes local loop controller dynamics and detailed control sequences. The testbed leverages a Modelica-based building model that allows controllers to be accurately simulated along with the building heat transfer physics and thermodynamics. Uncertainty models were integrated with the deterministic models of the building and the control sequence at small time scales to represent frequencies in which a real-world building automation system (BAS) samples its signals. Challenges associated with implementing uncertainty quantification on such a detailed model are discussed along with proposed solutions. Furthermore, control sequences for air distribution and terminal systems in HVAC aim to achieve a balance in the system outputs, i.e., maintain thermal comfort and indoor air quality (IAQ) with minimal energy use. ASHRAE Guideline 36 (G36) - High-Performance Sequences of Operation for HVAC Systems - is the result of ASHRAE research project 1455-RP intended to develop standardized sequences of operation to achieve more effective use of existing controls. This work complements G36 by evaluating the influence of the uncertainty inherent in the control components (e.g. sensors and actuators) on the system outputs of a multiple zone variable air volume (VAV) system. The system outputs under study were zone air temperature, relative humidity, indoor air quality (IAQ, represented by CO2 concentration), and site electricity use. To evaluate the effects of uncertainty in HVAC systems with advanced sequences of operation, this work applies a Monte Carlo uncertainty analysis to a testbed programmed with G36 control sequences. The impact of uncertainty was quantified using annual simulations. Specification of the accuracy levels in the components of the control system were evaluated by the means of: 1) uncertainty analysis for three different severities of accuracy in the components - low, medium, and high - to identify relation between performance requirements and component accuracy, and 2) sensitivity analysis to identify the sensors and actuators where the impact of uncertainty on the system outputs is most influential. Finally, for standardized HVAC system sequences of operation to achieve their potential benefits, verification of the implementation and state of tuning is currently required for every installation. Indices for control loop performance assessment (CLPA) provide a way to evaluate individual control loops. In systems that use a large number of control loops, identification of poorly performing loops using CLPA indices needs to be reported in conjunction with additional information that enables prioritization of retuning efforts. This work evaluates control loop performance on two levels. First, the Harris index is used to assess individual control loop performance. The index is sensitive to several parameters that have to be adjusted correctly to give the best results. Procedures for selecting index parameters are described. Second, a system-level regression model is developed that combines individual loop performance to assess system-level impact on thermal comfort, IAQ, and energy use. An extensive database was generated by systematically detuning the eleven control loops in the model. The database allowed for investigation of the link between individual control loop performance and system-level performance metrics. In turn, this information can be used to better prioritize retuning and to explain the interaction between control loops.