Presented at the 2nd International Symposium on Innovative Approaches in Scientific Studies (ISAS2018-Winter), Samsun, Turkey, Nov 30, 2018

SETSCI Conference Proceedings, 2018, 3, Page (s): 907-910 , https://doi.org/

Published Date: 31 December 2018    | 1470     10

The successful estimation of future electricity consumption has a crucial importance in the energy planning.
Because, in order to meet rising energy demand, policy makers should formulate electricity supply policies and make critical
decisions and develop new strategies. This study aims to compare prediction capabilities of three different techniques in order
to forecast electricity energy consumption of Turkey. These three techniques are; Autoregressive Integrated Moving Average
(ARIMA), grey prediction model GM (1,1) and Linear Regression (LR) analysis. Yearly electricity consumption data of
Turkey between 1970 and 2017 were obtained from the Turkish Electricity Transmission Company (TEIAS). The future
electricity demand for a period of 6 years from 2018 to 2023 has been predicted. ARIMA (1,1,2) model showed best results in
terms of highest value of coefficient of determination (R2 = 99.9 %). The results of the study can help decision makers in
planning future applications.  

Keywords - ARIMA, electricity consumption, estimation, grey model, linear regression analysis

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