Document
Predicting Electricity Consumption Using Load Profiling Clustering Method
Linked Agent
Hilal, Sawsan , Thesis advisor
Ksantini, Riadh, Thesis advisor
Language
English
Extent
[1], 8, 144, [1] Pages
Place of institution
Sakhir, Bahrain
Thesis Type
Theses (Master)
Institution
"University of Bahrain, College of Science Environmental and Sustainable Development program
English Abstract
Abstract:
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.
Member of
Identifier
https://digitalrepository.uob.edu.bh/id/02bd4703-e9a8-4a79-84df-74284bd02ed0