Data-Driven Sensor Calibration Method of VAV Terminal Unit
نویسندگان
چکیده
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 VAV systems, indoor loads carbon dioxide (CO2) concentrations were predicted, Bayesian markov chain monte carlo (MCMC)-based was used. used for analysis development collected using dynamic energy simulation tool, TRNSYS 17. Data MCMC algorithms analyzed developed R Studio. comfort consumption offset error effect supply flow rate units. A distance function model. algorithm. performance evaluation methods utilized simulations data. It confirmed that be possible case errors.
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ژورنال
عنوان ژورنال: ????????? ???
سال: 2022
ISSN: ['1976-5622', '2233-4335']
DOI: https://doi.org/10.7836/kses.2022.42.5.073