چكيده به لاتين
As the most active industry in any country, the power generation sector has high energy consumption and pollution. In Iran, the increasing demand for energy and high pollution by power plants has caused great importance to pay attention to these industries' energy intensity and pollution. Understanding the effects of various factors on energy consumption and pollution is essential to provide a suitable solution to reduce energy intensity and carbon dioxide emissions. Therefore, the effects of activity, production structure, energy intensity, fuel composition, and fuel emission factor on energy consumption and carbon dioxide emissions in each power plant from 1990 to 2017 -by type of ownership- and from 1999 to 2006 -by type of infrastructure-, was analyzed in four separate processes using the logarithmic mean Divisia index (LMDI) decomposition methods. The results showed that the effect of activity had the most effect on the high correlation coefficient. The effect of the fuel emission factor had the least effect on both variables. Besides, by calculating the energy intensity and carbon dioxide emission index of power plants and comparing it with the Decomposition results, It was confirmed that the private sector (in the ownership) and combined cycle power plants (in the infrastructure) have the best efficiency and pollution rate. Then, several highly cited articles in the field of policy in the electricity sector based on the (LMDI) method were collected, and the best of them were selected by using scientometrics to be used to provide a suitable solution. In the end, these solutions are presented based on the results of Decompositions, taken from selected articles, and under the laws in Iran to control energy consumption and carbon dioxide emissions in the electricity sector.
