Zulkafli, Nur Izyan and Noordin Saleem, Siti Nur Afifah and Tee, Boon Tuan and Sukri, Mohamad Firdaus and Mohd Tahir, Musthafah and Muhajir, Asjufri and Sulaima, Mohamad Fani and Piotr Hanak, Dawid (2024) Multiple linear model analysis of indoor air quality for air conditioning system in office building. Chemical Engineering Transactions, 113. pp. 127-132. ISSN 2283-9216
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Abstract
The building performance is measured through the power consumption of the air conditioning system and indoor air quality (IAQ) of the building spaces to provide sufficient cooling while at the same time satisfying thermal comfort. The multiple linear model of Piecewise linear (PWL) and Multiple Linear Regression (MLR) model is used to accurately estimate the power consumption of the air conditioning system considering IAQ parameters such as carbon dioxide concentration, indoor air temperature, and humidity. The IAQ parameters are usually modelled individually for the building without proper correlation with the power consumption of the air conditioning system. This problem makes the modelling results unrealistic to the building performance solutions. This paper focuses on identifying the relationship between power consumption with integrated IAQ parameters of CO2 concentration, air temperature, and humidity for Air Conditioning Mechanical and Ventilation (ACMV) system in the office building. The results demonstrate the power consumption estimation model considering IAQ parameters for different time zones is accurate and acceptable with a percentage difference of less than 1 % from the real data. The power consumption estimation model can be used to predict future power consumption with optimum range values for IAQ parameters for sustainable utilisation of energy.
Item Type: | Article |
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Uncontrolled Keywords: | Indoor Air Quality (IAQ), Power consumption estimation, Air Conditioning Mechanical and Ventilation (ACMV), Multiple Linear Regression (MLR), Piecewise Linear Model (PWL) |
Divisions: | Faculty Of Mechanical Technology And Engineering |
Depositing User: | Norfaradilla Idayu Ab. Ghafar |
Date Deposited: | 08 Oct 2025 00:37 |
Last Modified: | 08 Oct 2025 00:37 |
URI: | http://eprints.utem.edu.my/id/eprint/28953 |
Statistic Details: | View Download Statistic |
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