Investigation of Performance Effect of Input Diversity on Long Term Electricity Demand Forecasting

ALTINÖZ Ö. T., Mengusoglu E.

23nd Signal Processing and Communications Applications Conference (SIU), Malatya, Turkey, 16 - 19 May 2015, pp.1098-1101 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/siu.2015.7130026
  • City: Malatya
  • Country: Turkey
  • Page Numbers: pp.1098-1101
  • Keywords: long term forecasting, electricity demand, neural network, ARTIFICIAL NEURAL-NETWORKS
  • TED University Affiliated: Yes

Abstract

The long term electricity demand forecasting is evaluated by using past demand and weather data. The aim of this study is to present the effect of the variety of inputs on performance. Therefore neural network models are evaluated due to their performance and common acceptance. Different varieties of inputs are applied to the model and results are compared with each other.