Forecasting Turkey's Short Term Hourly Load with Artificial Neural Networks


BİLGİÇ KÜÇÜKGÜVEN M., Girep C. P. , ASLANOĞLU S. Y. , AYDINALP KÖKSAL M.

2010 IEEE PES Transmission and Distribution Conference and Exposition - Smart Solutions for a Changing World, Louisiana, United States Of America, 19 - 22 April 2010 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Louisiana
  • Country: United States Of America

Abstract

Load forecasting is important necessity to provide economic, reliable, high grade energy. In this study, short term hourly load forecasting systems were developed for nine load distribution regions of Turkey using artificial neural networks (ANN) approach. ANN is the most commonly preferred approach for load forecasting. The mean average percent error (MAPE) of total hourly load forecast for Turkey is found as 1.81%.