Optimal carbon capture and storage contracts using historical CO2 emissions levels

Abstract

In an effort to reduce carbon dioxide (CO2) emissions to the atmosphere, carbon capture and storage (CCS) technology has been developed to collect CO2 from emissions generators and store it underground. Recent proposed legislation would limit the volume of emissions generated from power sources, effectively requiring some sources to participate in CCS. Both emissions sources and storage operators require incentives to enter into contracts to capture excess emissions at the source, and transport and store the CO2 underground. As the level of emissions from power plants is stochastic and carryover into future time periods is expensive, we develop a newsvendor model to determine the optimal price and volume of these contracts to maximize the expected profit of the storage operator and encourage the participation of multiple emissions sources. Because the storage operator has a limit on the amount of CO2 that can be injected each month, this limit affects the allocation of the optimal contract amounts between the emitters. The distribution of emissions and relative costs of transportation also influence the optimal policy. In addition to analytical solutions, we present data-driven methods for using correlated emissions data to determine the optimal price and volume of these contracts.