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SETSCI - Volume 1 (2017)
ISMSIT2017 - International Symposium on Multidisciplinary Studies and Innovative Technologies, Tokat, Turkey, Dec 02, 2017

Estimation of Electricity Consumption by Regression and Artificial Neural Networks Approaches (ISMSIT2017_54)
Ümmü Gülsüm Eraslan1*, Figen Balo2, Büşra Çetin3, Ukbe Ü. Uçar4
1Fırat University, Elazığ, Turkey
2Fırat University, Elazığ, Turkey
3Fırat University, Elazığ, Turkey
4Fırat University, Elazığ, Turkey
* Corresponding author: gulsumeraslan7@gmail.com
Published Date: 2017-12-08   |   Page (s): 235-238   |    166     4

ABSTRACT Aim of the study: It is important to be able to plan the production transmission and distribution necessary for uninterrupted electricity and to use the electricity more efficiently and to make demand forecasts. For this reason, it is aimed to estimate the electric energy demand for Elazığ province for 10 years. 

Material and Methods: In this study, electricity consumption for the years 20017-2026 was estimated by using artificial neural networks and multiple regression methods considering the data covering the years 2002-2016 for Elazığ province. In the application MATLAB program is used. 

Results: The results obtained with the artificial neural networks method are compared with the regression technique and show that artificial neural networks are a better method of predicting electrical energy consumption. 

KEYWORDS Electric Energy Estimation, Regression Analysis, Artificial Neural Networks
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