Zulkafli, Nur Izyan and Hashim, Muhammad Fikri and Sulaima, Mohamad Fani and Jali, Mohd Hafiz and Ahmad Izzuddin, Tarmizi and Jayiddin, Nur Saleha and Md Lasin, Azmi and Iskandar, M Tarmidzi (2025) Predicting power consumption of cryogenic compressors using multiple linear regression in machine learning. Chemical Engineering Transactions, 122. pp. 235-240. ISSN 2283-9216
![[img]](http://eprints.utem.edu.my/style/images/fileicons/text.png) |
Text
02190311220251657362857.pdf Download (1MB) |
Abstract
Compressor performance is being evaluated based on its power consumption and other operational parameters to meet load demand efficiently while consuming less power. Without proper correlation with other operational data, it is difficult to predict future power consumption that may lead to a low performance of compressors. The Multiple Linear Regression (MLR) analysis in Altair AI Studio software is being used as a model to predict power consumption for four compressors with two different models by considering mass flow rate, suction and discharge temperature, and pressure as its dependent variables. The set of data has been split into two, which are training and testing, at a ratio of 90:10, respectively. This study resulted in a low percentage difference between the predicted and actual power consumption of those four compressors, which are 1.46 %, 1.40 %, 2.00 %, and 2.25 % for Compressor 1, Compressor 2, Compressor 3, and Compressor 4, respectively. The MLR of the compressor power consumption model can be utilized to predict its future power consumption to move towards more sustainable and low-carbon emissions.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Power consumption prediction, Machine learning, Predictive modeling |
| Divisions: | Faculty Of Mechanical Technology And Engineering |
| Depositing User: | Sabariah Ismail |
| Date Deposited: | 23 Feb 2026 02:01 |
| Last Modified: | 23 Feb 2026 02:01 |
| URI: | http://eprints.utem.edu.my/id/eprint/29546 |
| Statistic Details: | View Download Statistic |
Actions (login required)
 |
View Item |