Modelling of Turkey’s Energy Consumption Using Artificial Neural Networks

Abstract

Energy is one of the most important inputs to maintain social and economic improvement in the countries. It is necessary that energy demand should be performed at the right time economically and be of good quality and respectful if increasing environmental consciousness in order to preserve national development and a high standard of living. Turkey's energy use is expected to increase by 50% over the next decade. Turkey's installed capacity has exceeded 88 GW as of January 2019, representing a threefold increase in 15 years. For this reason, an accurate prediction of the consumed energy is critical. Predictions of energy demand in developing countries show more deviations than in developed countries. The essential scope of this study is to develop a new electricity prediction model for Turkey, which has not been used in the literature before. In the study, the global system for mobile communications (gsm) subscribers, fertility rate and cultivated land per capita have been used for the first time in the literature as variables. Factors resulting from health-ecological problems as well as cultural, social and economic changes and differences in Turkey were included in the model to obtain more realistic results. The model was developed between 1975 and 2016, and 73 different economic and social variables were evaluated using artificial neural networks (ANN). The model was established by reducing the number of variables according to the weight ratio. Then, two different cases have been created and tested. Turkey’s electricity consumption has been predicted accurately until 2023 using SPSS Clementine software.