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Research Article Open Access

Estimation of Electricity Consumption by Regression and Artificial Neural Networks Approaches

1Fırat University
✉ Corresponding author: Ümmü Gülsüm Eraslan · gulsumeraslan7@gmail.com
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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. 

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Cite this article

Eraslan, Ü. G., Balo, F., Çetin, B., & Uçar, U. Ü. (2017). Estimation of Electricity Consumption by Regression and Artificial Neural Networks Approaches. In International Symposium on Multidisciplinary Studies and Innovative Technologies (pp. 235–238). SET Technology.

Article History

Published
8 Dec 2017

License

© 2017 SET Technology. This article is distributed under the terms of the CC BY 4.0.

Research Contributions (2019+)Peer reviewed by at least two reviewers
Open AccessCC BY 4.0
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