Long run energy demand in Iran: a scenario analysis

Abstract

Iran as an energy-rich country faces many challenges in the optimal utilization of its vast resources. High rates of population and economic growth, a generous subsidies program, and poor resource management have contributed to rapidly growing energy consumption and high energy intensity over the past decades. The continuing trend of rising energy consumption will bring about new challenges as it will shrink oil export revenues restraining economic activities.This calls for a study to explore alternative scenarios for the utilization of energy resources in Iran. In this study, we model demand for different types of energy in Iran using a technoeconomic or end-use approach and develop two business-as-usual and efficiency scenarios for the period 2005-2030.The results indicate that Iran has a huge potential for energy savings. Specifically, under the efficiency scenario, Iran will be able to reduce its energy consumption 40 percent by 2030.The energy intensity can also be reduced by about 60 percent to a level lower than the world average today. Furthermore, the energy savings under the efficiency scenario will generate significant additional revenues and will lead to a 45 percent reduction in CO 2 equivalent emissions by 2030 as compared to the BAU trend.

The effects of the energy price reform on households consumption in Iran

“…The direct energy subsidy has increased from 2 percent to 8 percent of the government budget since 2004. Energy consumption produced 480 million tons of CO 2 -equivalent emissions in 2012, a figure that is expected to double by 2030 if the current trend continues (Moshiri et al, 2012). The high concentration of pollutants and the ensuing costs and risks, especially in high population density areas, have become a major concern to the public and to policy makers.…”

Machine Learning Modeling for Energy Consumption of Residential and Commercial Sectors

“…These studies include the household income [25], different energy carriers' price [26,27], GDP, population, and oil price, CO 2 emission, electricity and heat demands, household energy demand, and demographic behaviors of households [28]. The applied methods in these studies include various types of techno-economic or end-use approach [27], energy demand model [29], linear regression models [30], and ANN models were also developed as BU models [31]. Studies on ANN models address ANN as an accurate tool for modeling energy consumption in office and school buildings [32,33].…”

“…GDP in Iran has increased with an annual average rate of 5.5% from 1988 to 2008. According to the study in [27], the GDP growth rate will be 3.4% and 3% in 2020 and 2030, respectively.…”

Towards a Low Emission Transport System: Evaluating the Public Health and Environmental Benefits

“…Figure 6 shows the comparison of transport mode shares between the baseline scenario and the TTMP in 2030. The amount of fuel-saving in the urban bus fleet was estimated based on an average fuel intensity of 25 L/100 km and an average mileage of 250 km/day [59]. The most fuel saving is expected from reducing about 2.94 billion liters in gasoline consumption by cars and taxies.…”