Modeling the future costs of carbon capture using experts' elicited probabilities under policy scenarios

We use expert elicitations of energy penalties and literature-derived estimates of basic cost parameters to model the future costs of 7 types of carbon capture technology applied to coal power plants. We conduct extensive sensitivity analysis to assess the effects of various parameters on additional levelized electricity costs ($/MWh) and costs of avoided CO2 emissions ($/tCO2) in 2025. Although the expert elicitation of energy penalties under various policy conditions spans a considerable range, we find that costs are more sensitive to assumptions about overnight capital costs and discounting. We run Monte Carlo simulations to specify a distribution of the minimum costs of capture across these 7 technologies and find that in 74% of cases, the minimum cost of capture is determined by one of three technologies. Despite these concentrated outcomes, we see benefits to technology portfolio diversification in that a full portfolio of technologies approximately doubles the likelihood of achieving a $60/tCO2 cost target versus focusing on a single capture technology.