Data-Driven Sensor Calibration Method of VAV Terminal Unit

Hyo-Jun Kim; Young-Hum Cho

doi:10.7836/kses.2022.42.5.073

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2022 Vol.42, Issue 5 Preview Page

Data-Driven Sensor Calibration Method of VAV Terminal Unit VAV 터미널 유닛 시스템의 데이터 기반 센서 보정 방법

30 October 2022. pp. 73-80

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Abstract

The objective of this study is to develop a data-driven prediction model and sensor calibration method in variable air volume (VAV) terminal unit systems. Based on the operational data of VAV terminal unit systems, indoor loads and carbon dioxide (CO₂) concentrations were predicted, and a Bayesian markov chain monte carlo (MCMC)-based sensor calibration method was used. The operational data of a VAV terminal unit used for data-driven model analysis and development were collected using the dynamic energy simulation tool, TRNSYS 17. Data analysis and Bayesian MCMC algorithms were analyzed and developed using R Studio. The indoor comfort and energy consumption were analyzed for the offset error effect of supply air flow rate in VAV terminal units. A sensor error distance function was developed using a prediction model. The sensor calibration method was developed using the Bayesian MCMC algorithm. The performance evaluation of sensor calibration methods utilized simulations data. It is confirmed that sensor calibration was confirmed to be possible in case of supply air flow rate sensor errors.

Keywords

Variable air volume systme

Terminal unit

Sensor calibration

Supply air flow rate

키워드

변풍량 시스템

터미널 유닛

센서 보정

공급풍량

References

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Information

Publisher :Korean Solar Energy Society
Publisher(Ko) :한국태양에너지학회
Journal Title :Journal of the Korean Solar Energy Society
Journal Title(Ko) :한국태양에너지학회 논문집
Volume : 42
No :5
Pages :73-80
Received Date : 2022-09-19
Revised Date : 2022-10-18
Accepted Date : 2022-10-18
DOI :https://doi.org/10.7836/kses.2022.42.5.073

Journal of the Korean Solar Energy Society ISSN:1598-6411(Print) 2508-3562(Online) 한국태양에너지학회 논문집

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