impact of carbon tax and fossil fuel price on long-term development of iranian electricity supply system

introduction despite the abundant renewable energy sources, the iranian energy sector relies almost entirely on fossil fuel energy resources. power sector is dominant source of co2emissions and responsible for about 35% of total co2 emissions in the country. additionally, long-term electricity demand of iran is expected to grow quickly, which in turn requires extensive investment to meet the growing demand over the next decades. on the other hand, increasing domestic fossil fuel consumption had been a serious challenge due to high costs of oil and gas. current study pays particular attention to the possible penetration rates of renewable electricity technologies and their implications for fossil fuel consumption and co2 emissions. the analysis is performed by using an energy supply optimization model. different scenarios are defined to evaluate the impact of fossil fuel prices and carbon tax on utilization of renewable resources. materials and methods model for energy supply strategy alternatives and their generalenvironmental impacts (message) is applied in this study as a mathematical programming tool. message is a multi-objective optimization model used for energy system planning, energy policy analysis, and scenario development over medium to long-term periods. message was originally developed at international institute for applied systems analysis (iiasa) and the international atomic energy agency (iaea) added a user-interface to facilitate its application. in this methodology, the performance of a special technology is compared with its alternatives on a life cycle basis to identify how much of the available technologies should be expanded to meet the future energy demands.   reference energy system for iranian power sector reference energy system represents the structure of power system depicting energy chains, electricity generation technologies, resources required to meet electricity demand, and energy levels. at the resource level, natural gas, petroleum products, hydrogen, nuclear fuel, thermal coal and different renewable energy resources including hydropower, wind, solar, geothermal, and biomass can be mentioned. conversion level consists of various conventional and advanced thermal power plants and different renewable electricity technologies for centralized power generation. in addition, some distributed generation (dg) technologies are also considered for on-site generation of electricity. imports and exports of electricity are modeled at the transmission level. data and scenarios the required data and the main assumptions for the iranian power sector are presented in this section. different scenarios are then defined to determine the appropriate technology options and to quantify the implications of renewables’ contribution to fuel consumption and co2 emissions. the main assumptions of the different scenarios are as follows: reference scenario: this scenario refers to business-as-usual situation describing the development of power sector with constant fuel price level over the projected period. high fuel price scenario: we assume a rising trend for fossil fuel prices which are consistent with those developed by u.s. energy information administration. carbon tax scenario: fuel price is assumed to be the same as high fuel price scenario and a rising trend for carbon tax is used in this scenario from 8 $/tonne carbon at the base year to 50 $/tonne at the end of the study period. results natural gas combined cycle power plant holds the largest contribution almost in all conditions over the period of study, as it may reduce the investment cost of electricity supply system and benefit from the higher energy efficiency. hydropower is one of the leading power generation technologies of the future. the total amount of hydropower generation will increase continuously until the limit of its exploitation is reached. operation of gas turbines will also be attractive due to the technical possibilities of plants in terms of adjusting power level to meet the peak load demand. however, in a longer term perspective, the maximum potential of generation from pumped-storage hydropower is fully exploited and the share of gas turbine may be reduced. a gradual change is seen in the power system structure over a short to medium-term period in the high fuel price scenario. combined cycle power plants increases at a descending rate. in the long-term, the generation is characterized with the application of wind turbines and solar photovoltaic systems. carbon price in carbon tax scenario accelerate the employment of renewable energies. the contribution of renewables to electricity generation in 2045 will reach to 10%, 20%, and 35% of total generation in the reference, high fuel price, and carbon tax scenarios, respectively.when there is no carbon tax, advanced coal power plants will be competitive, due to the assumed coal-to-gas fuel price ratio and their costs applied. the fuel consumption is slowed down in the alternative scenarios by deployment of renewable energies (24-42% reduction compared to the reference case in 2045). in the reference scenario, total emission reaches 217 million tonnes in 2045. in the alternative scenarios, between 38 to 93 million tonnes of carbon dioxide per year could be avoided compared with the reference case by 2045. this is as a result of renewable energy deployment. total amount of co2 emissions and carbon intensity are shown in figure 1.       figure 1. total co2 emissions and carbon intensity in different scenarios     conclusion this paper mainly focuses on the future development of electricity supply system in iran. it also explores the prospects for development of renewable electricity technologies and their implications for fossil fuel consumption and co2 emissions over the next three decades. different scenarios are investigated to evaluate how renewable energy utilization can be affected by technology development, fossil fuel prices, and carbon tax. the assessment of new energy technologies are provided by using message, a cost minimizing mixed-integer programming model. results of the model reveal that renewable energy technologies will contribute to supply 10-35% of total electricity demand by 2045. the average co2 emissions per unit of electricity generated can be reduced by 30-70%.