| Issue |
E3S Web Conf.
Volume 336, 2022
The International Conference on Energy and Green Computing (ICEGC’2021)
|
|
|---|---|---|
| Article Number | 00040 | |
| Number of page(s) | 15 | |
| DOI | https://doi.org/10.1051/e3sconf/202233600040 | |
| Published online | 17 January 2022 | |
Energy Consumption Patterns and Inter-Appliance Associations using Data Mining Techniques
1 Mouly Ismail Univeristy, ENSAM, MOROCCO MEKNES
* e-mail: abassi.mri@gmail.com
** e-mail: ahmed0arid@gmail.com
*** e-mail: m.laraki@edu.umi.ac.ma
**** e-mail: h.benazza@umi.ac.ma
In this paper, we propose to model the behaviors of Moroccan consumers in terms of energy consumption in different Moroccan buildings using the open MORED (A Moroccan Building Electricity Dataset) dataset as a data warehouse. The techniques used are Machine Learning Algorithms and Data Mining Techniques. The results obtained in this paper allow us to understand the behavior of a Moroccan consumer in terms of energy consumption and the use of appliances in the home. Inter-Appliance Association and Peak Hours detected in this study will be used later to develop an Energy Management System specifically for a Moroccan building. This can lay the foundation for efficient Energy Demand Management while improving end-user participation.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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