Research On CCS Investment Decision Of Coal-fired Power Plant Based On Fuzzy Real Options

Carbon Capture and Storage（CCS）technology provides a realistic choice for meeting energy and environmental challenges and achieving the 2°C temperature rise control target by 2050.The huge emission reduction potential combined with the near-zero CO₂emissions that can achieve the use of fossil energy makes it an important technological option for achieving global low-carbon development,especially for"coal-rich"countries like China.However,CCS investment is affected by many factors such as technological level,investment costs,operation and maintenance costs,implementation of supporting projects,changes in supply and demand of fossil fuels,fluctuations in carbon emissions trading,and policies and regulations.CCS investment faces great uncertainty.In this context,objectively evaluating the value of CCS investment and considering the subjective preferences of investors are of great practical significance for the scientific decision-making of CCS investment.In order to break through the lack of non-stochastic uncertainties in the CCS investment decision-making of traditional real options,the triangular fuzzy number and binary tree real option model are combined to construct a fuzzy real option model framework for CCS investment decision-making,and the model and Judging rules for reliability verification.In the single-stage analysis process,a random variable and four fuzzy variables are introduced to define the CCS investment project net present value formula and real option pricing model,and the investment decision rules under the fuzzy real option method are given.The empirical analysis is used to verify the reliability of the model and the judgment rules,and the superiority of the fuzzy real option method is obtained through the change confidence levelγanalysis.In the two-stage analysis process,by introducing a random variable and two fuzzy variables to define the net present value formula of CCS-EOR project and the compound real option pricing model,a causal compound binary tree pricing model was constructed,which was calculated through empirical analysis.The multi-stage CCS-EOR investment project’s project value is compared and analyzed with the single stage.The research shows that:（1）Project value valuation under the framework of fuzzy real options is affected by left spreadα,right spreadβ,and confidence levelγ.The largerαandβ,the greater the scope of change in project value.The greater the value ofγ,the lower the ambiguity of the parameters,the lower the uncertainty of the project value,and the higher the investor’s grasp of the project value.（2）The introduction of fuzzy numbers improves the traditional NPV method to underestimate the value of the project,and the real option method(in the case ofγ=0.8（Bottom）The decision rules that come out look the same.But when the confidence levelγchanges to[0,0.68]within the value range,investment decisions need to consider individual subjective factors such as investors’risk appetite and the estimation of the project’s future cash flow.（3）Multi-stage fuzzy real options.On this basis,the change process of the project itself is considered,and the impact of the change of the project over time on the value of the project is more accurately measured.This method is more suitable for a flexible and changeable investment environment,especially for business activities with strong policy dependence,such as investment and transformation of CCS projects.For uncertain factors that cannot be portrayed with randomness,investors can make reasonable estimates of the future based on risk appetite,management experience,and internal and external information,thereby improving the accuracy and effectiveness of investment decisions.This study provides a new theoretical basis for option pricing.The subjective uncertainty is regarded as a fuzzy number,which effectively overcomes the shortcomings of traditional real options.