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Abstract
Control of HVAC systems is critical to building energy efficiency and indoor environment. Almost all control systems require real-time measurements. However, the measurements inherently contain errors that inevitably impact the outputs of control systems. Therefore, it is of great interest to analyze the impacts of the measurement sensitivity and uncertainty on the control of HVAC systems. This article presents a sensitivity and uncertainty analysis method for HVAC optimal control strategies. The critical measurements in a control strategy are identified by using sensitivity analysis. The uncertainty analysis provides information for further risk analysis. A modified exponentially weighted moving average filter is developed and adopted to reduce the uncertainty of control strategies. The sensitivity and uncertainty analysis is conducted on demand-controlled ventilation strategies for multi-zone office buildings. Improvements of the control strategies based on the analysis results are also conducted. Results demonstrate the sensitivity and uncertainty analysis are effective in evaluating control strategies. The accuracy of the control strategy is significantly improved, and the uncertainty is reduced.
Acknowledgments
The research presented in this article is financially supported by the Research Grant Council (RGC) of the Hong Kong SAR (grant 5276/12E). The authors would like to thank Kai Shing Management Services Limited for the support to the site study.
Kui Shan, MSc, is PhD Student. Shengwei Wang, PhD, Member ASHRAE, is Chair Professor. Fu Xiao, PhD, Member ASHRAE, is Assistant Professor. Yongjun Sun, PhD, is Postdoctoral Fellow.