Minimizing data collection for field calibration of steady-state virtual sensors for HVAC equipment

Abstract

The paper presents an algorithm to minimize the amount of data collection for calibration of steady-state virtual sensors when obtained during normal operation of HVAC equipment in the field. If virtual sensors were calibrated using laboratory data, the amount of the calibration data could be minimized using design of experiment techniques. However, these techniques are not applicable to data from field operating equipment since most of the operating conditions are not controllable (e.g., ambient temperature, loads). In this paper, an algorithm to minimize the data collection period for calibration of steady-state virtual sensors is developed based on sensor accuracy, reliability and applicability. Application of the method is demonstrated for calibration of hourly electricity consumption virtual sensors for 3 packaged air conditioners that are serving a small commercial building, and the method terminated the calibration process after about 3 weeks of data collection for all units with very accurate estimates of electricity consumption.