Development and Performance Evaluation of a Steady-State Virtual Sensor for Predicting Wall Surface Temperature in Light Commercial Buildings with an Open Space

Authors

  • Denchai Woradechjumroen Durham School of Architectural Engineering and Construction, University of Nebraska-Lincoln
  • Haorong Li Durham School of Architectural Engineering and Construction, University of Nebraska-Lincoln
  • Yuebin Yu Durham School of Architectural Engineering and Construction, University of Nebraska-Lincoln

Keywords:

MLR, Retail stores, RTUs, Virtual sensor, Supervisory control

Abstract

Multi-zone layout is commonly designed for low-rise cubicle offices or big-box retail stores. These buildings are served by multiple rooftop units (RTUs) to supply heating and cooling. Regarding this open space layout without interior walls between zones, heat balance effect between a zone and adjacent zones is occurred rather than general multi-zones with interior walls. This effect probably causes simultaneous cooling and heating or cooling fighting because each RTU has individual and uncoordinated control resulting in excessive energy use and shorter cycling operations of RTUs. To measure this effect and solve the problem, this article proposes a virtual sensor for predicting wall surface temperature by using a steady-state equation based on multiple linear regressions (MLR). Utilizing rich data of practical operations obtained from the simulation of multiple RTUs, MLR can be used to accurately extrapolate within the range of the training data. Using the building simulation platform based on heat, air and Moisture laboratory (Hamlab) without RTU operations, this simulated data are used to validate the developed model. To further evaluate the model performance, the three control modes of the multiple RTUs including undersized, right-sized and oversized capacities of multiple RTUs are simulated and studied. The results show that the proposed virtual sensor improves the implementation performances of dynamic virtual wall surface temperature sensor under off-control conditions around 16 to 20% based on goodness of fit (G). In addition, the proposed method can be applied as a tool in predicting wall surface temperatures of special cooling and heating wall in renewable energy areas.

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Published

2018-06-29

How to Cite

Woradechjumroen, D., Li, H., & Yu, Y. (2018). Development and Performance Evaluation of a Steady-State Virtual Sensor for Predicting Wall Surface Temperature in Light Commercial Buildings with an Open Space. International Journal of Building, Urban, Interior and Landscape Technology (BUILT), 3, 5–22. Retrieved from https://ph02.tci-thaijo.org/index.php/BUILT/article/view/170264