Modeling of energy consumption based on economic and demographic factors: The case of Turkey with projections

Aydin G.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS, cilt.35, ss.382-389, 2014 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Derleme
  • Cilt numarası: 35
  • Basım Tarihi: 2014
  • Doi Numarası: 10.1016/j.rser.2014.04.004
  • Dergi Adı: RENEWABLE & SUSTAINABLE ENERGY REVIEWS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.382-389
  • Anahtar Kelimeler: Turkey, Primary energy consumption, Regression analysis, Modeling, Forecasting, PARTICLE SWARM OPTIMIZATION, GENETIC ALGORITHM, NEURAL-NETWORK, CO2 EMISSIONS, ELECTRICITY CONSUMPTION, GREY PREDICTION, TIME-SERIES, DEMAND, INTELLIGENCE, INTEGRATION
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

Modeling and forecasting of the primary energy consumption (PEC) play a vital role for policy makers and related organizations in developing countries such as Turkey. In this study, Turkey's PEC is modeled by regression analysis (RA) based on population (CP) and gross domestic product (GDP). The derived model is validated by various statistical approaches such as the determination coefficient, t-test, F-test, and residual analysis. Additionally, the performance of the derived model is assessed using mean absolute percentage error (MAPE), root mean square error (RMSE) and means absolute error (MAE). Three scenarios are used for forecasting Turkey's PEC in the years 2010-2025. For each scenario, various assumptions are made considering different growth rate for CP and GDP. Using the proposed model, Turkey' PEC is forecasted under different scenarios. The results show that the proposed model can be affectively used for forecasting of Turkey's PEC. The scenarios also show that the future energy consumption of Turkey would vary between 174.65 and 203.13 Mtoe in 2025. (C) 2014 Elsevier Ltd. All rights reserved.