Energy consumption forecast of Turkey using artificial neural networks from a sustainability perspective

DEMİRCİOĞLU M., EsIyok S.

INTERNATIONAL JOURNAL OF SUSTAINABLE ENERGY, cilt.41, sa.8, ss.1127-1141, 2022 (ESCI) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 41 Sayı: 8
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1080/14786451.2022.2026357
  • Dergi Adı: INTERNATIONAL JOURNAL OF SUSTAINABLE ENERGY
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus, Academic Search Premier, Aerospace Database, Agricultural & Environmental Science Database, CAB Abstracts, Communication Abstracts, Compendex, Environment Index, Geobase, Greenfile, INSPEC, Metadex, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.1127-1141
  • Anahtar Kelimeler: Energy consumption, prediction, sustainability, Artificial neural networks, ELECTRICITY CONSUMPTION, BEE COLONY, PREDICTION, DEMAND, MODELS
  • Çukurova Üniversitesi Adresli: Evet

Özet

As industrialization, population and living standards increase, energy becomes increasingly crucial. Therefore, modeling and forecasting of energy use is critical for countries. The studies carried out for energy consumption estimation were examined and indicators used in the literature were classified according to the three main dimensions of sustainability, social, economic, and environmental factors. Turkey's energy consumption estimates were made by four sustainability-based models. Input variables are GDP, electricity sales prices, import, population and temperature, while output variable is gross energy consumption. The models were tested and compared with Artificial Neural Networks (ANN). The best-performing Social-Economic-Environmental model has lowest MSE value (0.0001114) and highest R-2 value (0.99912). This model was used to forecast Turkey's energy use between 2021 and 2025.