Virtual in-situ calibration method in building systems

Abstract

Abstract Sensors play an important role in guiding building systems to achieve desired operation and efficiency. However, sensors are subject to continuous degradation and failures over time. Although a periodical calibration is needed, it is exceptionally difficult and/or impractical to many sensors with a conventional manual approach. Uncalibrated problematic sensors could significantly compromise the systems' performance and lead to unintended loss of energy efficiency in buildings. We propose a methodology, termed virtual in-situ calibration, to solve this critical issue. It is developed by mathematically extracting the characteristics of essential aspects involved in a calibration, including the environment assessment, benchmark establishment, and uncertainty quantification. A case study of a supply air temperature sensor in rooftop units illustrates the implementation process; the erratic uncertainty is reduced from ± 19.2 °C to ± 0.7 °C after the virtual in-situ calibration. The calibration method can be implemented online to significantly improve the reliability of sensor networks in buildings.