2 A Comparison of Stochastic and Deterministic Optimization Algorithms on the Virtual In-Situ Sensor Calibration in Building Systems (LV-17-C062)

Sungmin Yoon, University of Nebraska-Lincoln
Yuebin Yu, Ph.D., University of Nebraska-Lincoln
A virtual in-situ sensor calibration method has been recently studied in order to solve the practical problems of sensor calibration in building energy systems: (1) time and monetary cost; (2) disruption to a normal operation; (3) difficulty in accessing various embedded sensors in equipment; and (4) large quantity of sensors. The proposed in-situ calibration method is able to approximate the measure and establish benchmark values for a calibration statistically or by using system models, without removing the working sensor or adding reference sensors as in a conventional calibration.

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