Bulletin of Electrical Engineering and Informatics
Vol 12, No 2: April 2023

Data mining and analysis for predicting electrical energy consumption

Inteasar Yaseen Khudhair (University of Diyala)
Sanaa Hammad Dhahi (University of Kerbala)
Ohood Fadil Alwan (University of Diyala)
Zahraa A. Jaaz (Al-Nahrain University)



Article Info

Publish Date
01 Apr 2023

Abstract

In this study paper, the feasibility of constructing a complete smart system for anticipating electrical power consumption is created, as electricity's market share is expected to expand over the future decades. Smart grids and smart meters will help utility companies and their customers soon. New services and businesses in energy management need software development and data analytics skills. New services and enterprises are competitive. The project's electricity consumers are categorized by their hourly power usage percentage. This classification was done using data mining (five algorithms in specific) and data analysis theory. This division aims to help each group minimize energy use and expenditures, encourage energy-saving activities, and promote consumer involvement by giving tailored guidance. The intended segmentation is done through an iterative process using a computer classification computation, post-analysis, and data mining with visualization and statistical methodologies.

Copyrights © 2023






Journal Info

Abbrev

EEI

Publisher

Subject

Electrical & Electronics Engineering

Description

Bulletin of Electrical Engineering and Informatics (Buletin Teknik Elektro dan Informatika) ISSN: 2089-3191, e-ISSN: 2302-9285 is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the ...