Estimation of Net Energy Consumption in Turkey Using Different Indicators

Abstract

The main subject in this study is to obtain equations to predict net energy consumption of Turkey using energy sources and economic indicators by artificial neural network approach in order to determine the future level of the energy consumption and make correct investments in Turkey. In this study, three different models were used in order to train the artificial neural network. In the first model (Model 1), energy sources (e.g., natural gas, lignite, coal, hydraulic); in the second model (Model 2), gross national product; and in the third model (Model 3), gross domestic product, are used for the input layer of the network. The net energy consumption is in the output layer for all models. In order to train the neural network, economic and energy data for the last 37 years (1968-2005) is used in network for all models. The aim of using different models is to estimate the net energy consumption with high confidence to plan for future projections. The maximum mean absolute percentage error was found to be 1.992262, 1.110525, and 1.122048 for Model 1, Model 2, and Model 3, respectively. R2 values are obtained (0.999558, 0.999903, and 0.999903 for training data of Model 1, Model 2, and Model 3, respectively). The artificial neural network approach shows greater accuracy for evaluating net energy consumption based on economic indicators. Also, obtained results in this study were compared with results of similar studies using various techniques.