Predicting Electricity Consumption Using Load Profiling Clustering Method

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AuthorAljowder, Esra Jasim
metadata.dc.contributor.department"University of Bahrain, College of Science Environmental and Sustainable Development program
metadata.dc.date.accessioned2026-09-20T15:44:19Z
Publication date2023
Degree levelMaster
AbstractAbstract: Energy consumption is considered one of the essential topics of energy systems which gained high attention after the energy crisis in 1970’s. It has been shown that energy consumption throughout the world is rapidly increasing. The field of smart meter data analytics is considered as a relatively recent field that grew recently due to the importance of the data generated from smart meters and with the progress in highperformance computing which made it possible to efficiently and effectively use deep neural networks to extract more beneficial knowledge and patterns from collected massive data within the smart grid. Hence it became crucial to analyse the energy consumption trends.
metadata.dc.identifier.otherhttps://digitalrepository.uob.edu.bh/id/02bd4703-e9a8-4a79-84df-74284bd02ed0
metadata.dc.identifier.otherDrupal node 1946
metadata.dc.identifier.otherhttps://digitalrepository.uob.edu.bh/en/dar/predicting-electricity-consumption-using-load-profiling-clustering-method
metadata.dc.identifier.urihttp://165.227.56.122/handle/123456789/6169
Languageen
Linkhttps://digitalrepository.uob.edu.bh/en/_flysystem/fedora/2024-10/predicting-electricity-consumption-using-load-profiling-clustering-method.pdf
TitlePredicting Electricity Consumption Using Load Profiling Clustering Method
TypeMaster's Thesis
CollegeCollege of Science
DepartmentEnvironment and Sustainable Development Program

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