Electrical Energy Demand Forecasting Using Artificial Neural Network

Unutmaz Y. E. , Demirci A. , Tercan S. M. , Yumurtacı R.

3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications, HORA 2021, Ankara, Turkey, 11 - 13 June 2021 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/hora52670.2021.9461186
  • City: Ankara
  • Country: Turkey
  • Keywords: Artificial Neural Networks, Electricity Demand Forecasting, Load Forecasting Methods, Training Data Set


© 2021 IEEE.The continuous development of technology, population growth, and increased economic comfort enlarge the energy demand. The welfare and economy of both the producer and the consumer need to meet the increasing energy need by making investments and planning with the correct predictions. In this study, the electricity demand forecast is made with the help of Artificial Neural Networks (ANN). In order to increase the accuracy, educational data sets were created with historical electricity consumption data, taking into account social, economic, technological, and demographic factors. The forecasting method developed was applied to Düzce, Turkey's developing provinces. The 15-year electrical energy demand of the region was estimated with the ANN-based method. The results have been evaluated in detail.