A novel modeling based real option approach for CCS investment evaluation under multiple uncertainties

In this study, a trinomial tree modeling-based real option approach was developed to evaluate the investment in CCS retrofitting for two typical types of power plants from the perspective of power generation enterprises. A method based on the cumulative probability was proposed using trinomial decision tree calculations for the exercising of options in order to evaluate the optimal retrofit timing. Uncertainties in carbon prices, government incentives, annual running time, power plant lifetime, and technological improvements were considered. From the result, the cost saving effect of CCR pre-investment was apparent. When the current carbon price increased to 350.0 RMB/ton CO2, a power plant with CCR pre-investment would execute CCS retrofitting immediately, while this value would have to increase to 371.8 RMB/ton CO2 for the SC scenario. The two typical types of power plants were not optimal for immediate investment in CCS technology in the current market situation. Given a full government subsidy, the critical carbon prices for SC and SC + CCR were 239.2 and 230.0 RMB/ton CO2, respectively, while the current carbon price in the voluntary emission reduction market was 3.5 RMB/ton CO2. By introducing CO2 utilization technology, the critical carbon prices fell to 195.5 and 186.3 RMB/ton CO2, but they were still not optimal for immediate investment. CCR pre-investment was conducive to CCS retrofitting deployment; this would be more significant when considering CO2 utilization technologies. The results indicated that a large gap existed between the carbon price needed for CCS retrofitting of both typical types of power plants and the current prices in the voluntary emission reduction market. Moreover, the results obtained could also provide useful information for the CCS policy-making of power enterprises in an uncertain environment.