An empirical analysis for Turkey?s energy demand projections

Energy needs has become increasingly crucial as we experience high economic growth, increases in population together with rapid urbanisation. As energy has been used in every sectors and electricity, which is an important energy type, can not be stored, it is essential to have projections in order to estimate the future of energy demand. Due to the fact that Turkey is an energy importing country, it is more significant to have such energy projections. Having accurate energy demand projections is also important for developing appropriate climate change mitigation policies.In this study, Turkey?s energy structure, in terms of energy sectors and resources, is investigated. The study also tries to analyse the renewable energy resources potential for Turkey. By taking energy and socio-economic factors, which are the main determinants of energy demand, into consideration, Turkey?s official energy projections are analysed. Also, by assessing the energy demand forecasting modelling techniques, models focusing on Turkish energy demand are investigated. In order to estimate energy demand for Turkey, we chose to employ artificial neural network technique, a type of artificial neural intelligence application. For this purpose, three different scenarios are developed. These are: `static scenarios?, where economic growth is assumed to be stable, `sustainability scenarios?, where energy intensities are assumed to be decreasing and finally `periodic-change scenarios?, where the economic growth is assumed to change during five different time periods by 2030. Besides, both static and sustainability scenarios are further investigated under high, medium and slow economic growth assumptions. Periodic-change scenarios also consist of two sub-scenarios, where energy intensities are assumed to decrease and stayed the same. All scenarios are also applied to all individual sectors (Housing, industry, agriculture and transportation) and natural resounces (Oil, coal and natural gas) The results of the energy demand estimations found by our models are compared with the offical estimations of the Ministry of Energy and Natural Resources (MENR). It is concluded that the MENR estimations are significantly higher than what we have found with our models.