Estimating transportation energy demand in Turkey via genetic algorithmi GHG emission for electric cars scenario and its climate change effect

Abstract

The aim of this thesis is to examine changes in transport energy demand, changes in the types of vehicles and the effect of this change on GHG emissions and climate change. According to Turkish Statistical Institute energy demand on highways in creases every year. Increase in population, GNP and developments on highways are the main reasons of this situation. Energy demand on highways is calculated with the help of the genetic algorithm in this thesis. The genetic algorithm performs in MATLAB. While calculating the energy demand, parameters of the expected values are collected from national and international reports and some regression models. Es timated energy demand shows that a need for electric vehicles has risen due to their diminishing effect on fuel oil usage. In order to analyze this situation at first number of electric vehicles is forecasted for the year 2050. Then the impact of the electric ve hicles is detailed with three different scenarios. Positive effect of electric vehicles is to decrease oil production and consumption. Thus, GHG emissions reduces definitely, but there will be an additional demand on electric generation which will still cause GHG emissions. The amount of additional emissions is operated in three different genera tion processes. Finally, it is observed that all of the scenarios have a positive impact on mitigating GHG emissions. Also, this impact is evaluated according to emission target of Turkey in Paris Agreement. The electric vehicles help Turkey to achieve the reduction target between 8 to %10 depending on electric generation process.