Energy Consumption Patterns and Inter-Appliance Associations using Data Mining Techniques

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 Techni...

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Veröffentlicht in:E3S Web of Conferences 2022, Vol.336, p.40
Hauptverfasser: Abdelfattah, Abassi, Ahmed, Arid, Maha, Laraki, Hussain, Ben-Azza
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Sprache:eng
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Zusammenfassung: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.
ISSN:2267-1242
2555-0403
2267-1242
DOI:10.1051/e3sconf/202233600040