Modeling and prediction of Turkey's electricity consumption using Artificial Neural Networks

Kavaklioglu K., Ceylan H., Ozturk H. K. , Canyurt C. E.

ENERGY CONVERSION AND MANAGEMENT, vol.50, no.11, pp.2719-2727, 2009 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 50 Issue: 11
  • Publication Date: 2009
  • Doi Number: 10.1016/j.enconman.2009.06.016
  • Journal Indexes: Science Citation Index Expanded, Scopus
  • Page Numbers: pp.2719-2727
  • Keywords: Electricity consumption, Artificial Neural Networks, Turkey, ENERGY DEMAND, ECONOMIC-GROWTH, CAUSALITY, GNP


Artificial Neural Networks are proposed to model and predict electricity consumption of Turkey. Multi layer perceptron with backpropagation training algorithm is used as the neural network topology. Tangent-sigmoid and pure-linear transfer functions are selected in the hidden and output layer processing elements, respectively. These input-output network models are a result of relationships that exist among electricity consumption and several other socioeconomic variables. Electricity consumption is modeled as a function of economic indicators such as population, gross national product, imports and exports. It is also modeled using export-import ratio and time input only. Performance comparison among different models is made based on absolute and percentage mean square error. Electricity consumption of Turkey is predicted until 2027 using data from 1975 to 2006 along with other economic indicators. The results show that electricity consumption can be modeled using Artificial Neural Networks, and the models can be used to predict future electricity consumption. (C) 2009 Elsevier Ltd. All rights reserved.