Model-Based Testbed for Uncertainty Quantification in Building Control Systems with Advanced Sequences of Operation

JOURNAL OF ARCHITECTURAL ENGINEERING(2022)

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摘要
As advanced control sequences are developed to improve the 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 paper describes the detailed development of a testbed for performing uncertainty quantification in heating, ventilating, and air-conditioning (HVAC) system operational parameters, which includes local loop controller dynamics and detailed control sequences at small time scales. The testbed was developed using a Modelica-based building model that allows controllers to be accurately simulated along with the building heat transfer physics. The model is demonstrated by applying it to uncertainty quantification in annual site electricity use and internal zone conditions, due to the inherent inaccuracies in system sensors and actuators. The results and the testbed are intended to aid others in the research community who may need a similar HVAC controls simulation testbed. (C) 2022 American Society of Civil Engineers.
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关键词
Uncertainty quantification, Modelica buildings library, Bootstrap, Heating, ventilating, and air-conditioning (HVAC) with advanced sequences of operation, Monte Carlo
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