The Economics of Power Sector Decarbonization: A Case Study for Kuwait

In this research activity fuel energies were used to evaluate CO 2 emissions resulting from the power stations in Kuwait. Also, the calculated CO 2 emitted was used to perform economic valuation for using amine-based carbon capture technology to reduce the CO 2 emissions from the power stations. Linear regression model was used to predict CO 2 emissions using fuels energies used in the power stations. The dependent variable is total CO 2 emissions from the power stations while the independent variables are the fuels energies of the fuels used to generate electricity. Regression analysis results showed that the model has strong goodness of fit and regression coefficients have high significance level. The regression model indicated that Heavy fuel oil has the highest effect on the total CO 2 emitted. If the heavy fuel oil consumption increases with 1 BBTU this will lead to an increase in the total CO 2 emission of 0.0817 kton. The power stations with high dependence on Heavy fuel oil had higher emissions than other power stations. On the other hand, when Natural gas consumption increases with 1 BBTU this will increase the total CO 2 emissions with 0.0592 kton. Natural gas is the best fossil fuel to reduce emissions since it has less CO 2 emissions at any level of fuel energy compared to other fossil fuels. It was found that Alzour South, Sabiya, and Doha West power stations have the highest CO 2 emissions in the power sector. The preliminary economic valuation to use post combustion carbon capture technology was performed for the three power stations considering two modes of transportation which are pipelines and trucks. The results indicated that the total costs of CO 2 avoided for Alzour South are approximately USD 1.23 billion, and USD 1.58 billion for pipelines and trucks transport respectively while for Doha West are USD 738.5 million, and USD 945.9 million for pipelines and trucks transport respectively.