Abstract
A dynamic partial equilibrium model, TIMES (The Integrated MARKAL-EFOM System), is built to optimize the energy system in a post-transition European country, the Czech Republic. The impacts of overall nine scenarios on installed capacity, capital and fuel costs, air quality pollutant emission, emission of CO2 and environmental and health damage are quantified for a period up to 2050. These scenarios are built around three different price sets of the EUA (EU allowance) to emit greenhouse gasses alongside a policy that retains the ban on brown coal mining in two Czech mines, a policy that will allow the re-opening of mining areas under this ban (i.e. within the territorial ecological limits), and a low natural gas price assumption. We found that the use of up until now dominant brown coal will be significantly reduced in each scenario, although reopening the coal mines will result in its smaller decline. With low EUA price, hard coal will become the dominant fuel in electricity generation, while nuclear will overtake this position with a 51% or even 65% share assuming the central price of EUA, or high EUA price, respectively. The low price of natural gas will result in an increasing gas share from an almost zero share recently up to about 42%. This stimulus does not however appear at all with low EUA price. Neither of these scenarios will achieve the renewable energy sources 2030 targets and only a high EUA price will lead to almost full de-carbonization of the Czech power system, with fossil fuels representing only 16% of the energy mix. The low EUA price will result in an increase in CO2 emissions, whereas the high EUA price will reduce CO2 emission by at least 81% compared to the 2015 reference level. Those scenarios that will result in CO2 emission reduction will also generate ancillary benefits due to reduction in air quality emissions, on average over the entire period, at least at 38€ per t of avoided CO2, whereas scenarios that will lead to CO2 increase will generate ancillary costs at least of 31€ per t CO2.
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