Carbon dioxide capture and storage planning considering emission trading system for a generation corporation under the emission reduction policy in China

Power generation corporations face challenges from emission reduction targets (ERTs) of government policy from the increasingly explicit demand for carbon dioxide (CO2) emission reduction. CO2 capture and storage (CCS) is receiving considerable attention as a potential greenhouse gas mitigation option for fossil-fuelled power plants. In this study, a mathematical model is built to select the proper plants to deploy CCS under the Emission Trading System. The model considers factors such as clean energy development, fuel price fluctuation and economic level growth in the next five years to maximise the profit of the whole corporation under the premise of fulfilling the ERT in China. The Black-Scholes option pricing theory is used to analyse the investment potential amid yearly carbon price fluctuations. A discrete bacterial colony chemotaxis algorithm is then used to solve the model. The model is illustrated by an example of 11 plants with 17 units subordinated to a certain corporation in Hebei, China. The results show that the CCS planning situations in three carbon-trading scenarios and their option values can effectively provide the investment strategy references for power generation corporations.