Intelligent Load Identification of Household-Smart Meters Using Multilevel Decision Tree and Data Fusion Techniques
Mohammed Hasan Aldulaimi1, Ibrahim Najem2,3, Tabarak Ali Abdulhussein4, M. H. Ali5, Asaad Shakir Hameed6, M. Altaee7, Hatıra Günerhan8
1Department of Computer Techniques Engineering, Al Mustaqbal University College , Babylon 51001, Iraq
2 Department of Computer Techniques Engineering, Al-turath University College, Baghdad 10021, Iraq
3 MEU Research Unit, Middle East University, Amman 11831, Jordan
4 Department of Accounting, College of Administrative and Financial Sciences, Imam Ja'afar Al-Sadiq University, Baghdad, Iraq
5 Department of Medical device technology Engineering, National University of Science and Technology, Thi Qar, Iraq
6 Performance Quality Department, Mazaya University College, Thi-Qar, Iraq
7Department of Medical device technology Engineering, Alfarahidi University, Baghdad, Iraq
8 Department of Mathematics, Faculty of Education, Kafkas University, Kars, Turkey
Emails: mohammed.hassan@uomus.edu.iq; Ibrahim.najim@turath.edu.iq; tabarak.ali@sadiq.edu.iq; mohammed.hasan@nust.edu.iq; asaad.hameed@mpu.edu.iq; m.altaee@alfarahidiuc.edu.iq; hatira.gunerhan@kafkas.edu.tr
Abstract
The DTA-LI system's fusion data method is crucial in the monitoring of appliance loads for the purposes of improving energy efficiency and management. Common home electrical devices are identified and classified from smart meter data through the analysis of voltage and current variations, allowing for the measurement of energy usage in residential buildings. A load identification system based on a decision tree algorithm may infer information about the residents of a building based on their energy usage habits. Better power savings rates, load shedding management, and overall electrical system performance are the results of the clusters' ability to capture families' purchasing patterns and geo-Demographic segmentation. The DTA-LI system's fusion data method presents a promising avenue for improving residential buildings' energy performance and lowering their carbon footprint, especially in light of the widespread use of smart meters in recent years.
Keywords: decision tree algorithm; Appliance load monitoring; smart meter; household; Data Fusion Techniques.