Forecasting net energy consumption using artificial neural network


Soezen A., Akcayol M. A. , Arcaklioglu E.

ENERGY SOURCES PART B-ECONOMICS PLANNING AND POLICY, vol.1, no.2, pp.147-155, 2006 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 1 Issue: 2
  • Publication Date: 2006
  • Doi Number: 10.1080/009083190881562
  • Title of Journal : ENERGY SOURCES PART B-ECONOMICS PLANNING AND POLICY
  • Page Numbers: pp.147-155

Abstract

The main goal of this study is to develop the equations for forecasting net energy consumption (NEC) using the artificial neural network (ANN) technique in order to determine the future level of the energy consumption in Turkey. Logistic sigmoid transfer function was used in the network. In order to train the neural network, population, and gross generation, installed capacity and years is used in input layer of network. The net energy consumption is in output layer. The input values in 1965, 1981, and 1997 are only used as test data to confirm this method. The statistical coefficient of multiple determinations (R-2-value) is equal to 0.9999 and 1 for training and test data, respectively. According to the results, the NEC using the ANN technique has been obviously predicted within acceptable errors. Apart from reducing the whole time required, the importance of the ANN approach is possible to find solutions that make energy applications more viable and thus more attractive to potential users. It is also expected that this study will be helpful in developing highly applicable and productive planning for energy policies.