Future Projection for Renewable Energy Share in Electricity Generation Using Artificial Neural Networks


MIZRAK ÖZFIRAT P., ARI D.

7th International Conference on Environmental Sciences and Renewable Energy, ESRE 2025, Madrid, İspanya, 23 - 25 Haziran 2025, cilt.643, (Tam Metin Bildiri) identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 643
  • Doi Numarası: 10.1051/e3sconf/202564303004
  • Basıldığı Şehir: Madrid
  • Basıldığı Ülke: İspanya
  • Manisa Celal Bayar Üniversitesi Adresli: Evet

Özet

Electricity generation is dependent on many different energy resources including fossil fuels, hydroelectric power, natural gas and renewable energy resources. Environmental considerations are increasing in today's world. Therefore, renewable energy resources and technologies follow an increasing trend. They are getting more into use and gain more importance. However, fossil fuels, natural gas and hydroelectric power still constitutes a major part of total electricity generation. In this study, electricity generation of Turkiye according to different types of energy resources are considered. The increasing trend in renewable energy resources is observed. Hence, in order to make a future projection for these resources, regression analysis and artificial neural networks are employed. The results of the two forecasting processes are compared in terms of forecast errors. Finally, estimates for renewable energy resources are provided for future.