ARIMA forecasting of primary energy demand by fuel in Turkey

Ediger V. S., Akar S.

ENERGY POLICY, cilt.35, sa.3, ss.1701-1708, 2007 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 35 Sayı: 3
  • Basım Tarihi: 2007
  • Doi Numarası: 10.1016/j.enpol.2006.05.009
  • Dergi Adı: ENERGY POLICY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus
  • Sayfa Sayıları: ss.1701-1708
  • Anahtar Kelimeler: primary energy demand, ARIMA forecasting, Turkey, GENETIC ALGORITHM APPROACH, TIME-SERIES MODELS, NATURAL-GAS DEMAND, EXERGY PRODUCTION, NEURAL-NETWORK, WIND-SPEED, PART 1, CONSUMPTION, GDP, CAUSALITY
  • Orta Doğu Teknik Üniversitesi Adresli: Hayır

Özet

Forecasting of energy demand in emerging markets is one of the most important policy tools used by the decision makers all over the world. In Turkey, most of the early studies used include various forms of econometric modeling. However, since the estimated economic and demographic parameters usually deviate from the realizations, time-series forecasting appears to give better results. In this study, we used the Autoregressive Integrated Moving Average (ARIMA) and seasonal ARIMA (SARIMA) methods to estimate the future primary energy demand of Turkey from 2005 to 2020. The ARIMA forecasting of the total primary energy demand appears to be more reliable than the summation of the individual forecasts. The results have shown that the average annual growth rates of individual energy sources and total primary energy will decrease in all cases except wood and animal-plant remains which will have negative growth rates. The decrease in the rate of energy demand may be interpreted that the energy intensity peak will be achieved in the coming decades. Another interpretation is that any decrease in energy demand will slow down the economic growth during the forecasted period. Rates of changes and reserves in the fossil fuels indicate that inter-fuel substitution should be made leading to a best mix of the country's energy system. Based on our findings we proposed some policy recommendations. (c) 2006 Elsevier Ltd. All rights reserved.