(679e) Flexible Carbon Capture Exploiting Dynamic Changes in Electricity Price
While power plants produce electricity from fossil fuels, they are responsible for more than 30% of the global CO2 emissions due to human activity. One way to prevent CO2 emission and reduce its harmful contribution to global warming and climate change is to capture the CO2 from the power plant flue gas using chemical separation. However, current capture processes are highly energy-intensive and need almost one-third of the electricity generated by the power plant itself. This is one of reasons why the carbon capture and storage (CCS) technology has not been commercially successful, albeit showing great potential for environmental benefits. In this work, we develop a framework for smarter design and operation of a flexible carbon capture process that changes its production capacity depending on the changes in electricity price. Given a forecast of electricity price over time, the operation of the capture process is scheduled to capture more CO2 when the electricity price is low, and capture less CO2 when the electricity demand and prices are high. This way, the power plant sustains a greater profit while reducing its CO2 emission to the atmosphere. The overall optimization problem is formulated as a mixed integer linear program (MILP) to make decisions and schedules for the dynamically operated capture plant under changing electricity price and demand forecasts. The model is further extended to explore the possibility of a distributed capture system with multiple smaller capacities which provide more options for flexible operation under electricity price changes.