LAPSE

LAPSE:2019.0397
Published Article
LAPSE:2019.0397
Performance of a Predictive Model for Calculating Ascent Time to a Target Temperature
Jin Woo Moon, Min Hee Chung, Hayub Song, Se-Young Lee
February 27, 2019
The aim of this study was to develop an artificial neural network (ANN) prediction model for controlling building heating systems. This model was used to calculate the ascent time of indoor temperature from the setback period (when a building was not occupied) to a target setpoint temperature (when a building was occupied). The calculated ascent time was applied to determine the proper moment to start increasing the temperature from the setback temperature to reach the target temperature at an appropriate time. Three major steps were conducted: (1) model development; (2) model optimization; and (3) performance evaluation. Two software programs—Matrix Laboratory (MATLAB) and Transient Systems Simulation (TRNSYS)—were used for model development, performance tests, and numerical simulation methods. Correlation analysis between input variables and the output variable of the ANN model revealed that two input variables (current indoor air temperature and temperature difference from the target setpoint temperature), presented relatively strong relationships with the ascent time to the target setpoint temperature. These two variables were used as input neurons. Analyzing the difference between the simulated and predicted values from the ANN model provided the optimal number of hidden neurons (9), hidden layers (3), moment (0.9), and learning rate (0.9). At the study’s conclusion, the optimized model proved its prediction accuracy with acceptable errors.
Keywords
artificial neural network (ANN), ascending time, heating system, predictive controls, setback temperature
Suggested Citation
Moon JW, Chung MH, Song H, Lee SY. Performance of a Predictive Model for Calculating Ascent Time to a Target Temperature. (2019). LAPSE:2019.0397
Author Affiliations
Moon JW: School of Architecture and Building Science, Chung-Ang University, Seoul 06974, Korea
Chung MH: School of Architecture and Building Science, Chung-Ang University, Seoul 06974, Korea [ORCID]
Song H: School of Architecture and Building Science, Chung-Ang University, Seoul 06974, Korea
Lee SY: School of Architecture and Building Science, Chung-Ang University, Seoul 06974, Korea
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Journal Name
Energies
Volume
9
Issue
12
Article Number
E1090
Year
2016
Publication Date
2016-12-20
Published Version
ISSN
1996-1073
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Original Submission
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PII: en9121090, Publication Type: Journal Article
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LAPSE:2019.0397
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doi:10.3390/en9121090
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Feb 27, 2019
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CC BY 4.0
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Feb 27, 2019
 
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Original Submitter
Calvin Tsay
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