Annals of Emerging Technologies in Computing | |
Analysis of Home Energy Consumption by K-Mean | |
Fahad Razaque ; Nareena Soomro ; Javed Ahmed Samo ; Huma Dharejo and Shoaib Shaikh | |
关键词: Load-Profiles; K-means; Clusters; Data Science; Data Set; | |
学科分类:电子与电气工程 | |
来源: International Association for Educators and Researchers (IAER) | |
【 摘 要 】
The smart meter offered exceptional chances to well comprehend energy consumption manners in which quantity of data being generated. One request was the separation of energy load-profiles into clusters of related conduct. The Research measured the resemblance between groups them together and load-profiles into clusters by k-means clustering algorithm. The cluster met, also called “Gender (Male/Female), House (Rented/Owned) and customers status (Satisfied/Unsatisfied)” display methods of consuming energy. It provided value information aimed at utilities to generate specific electricity charges and healthier aim energy efficiency programs. The results show that 43% extremely dissatisfied of energy customer is achieved by using energy consumption.
【 授权许可】
CC BY
【 预 览 】
Files | Size | Format | View |
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RO201901219688815ZK.pdf | 791KB | download |