(158g) Optimal Scheduling of Advanced Energy Plants with CO2 Capture

Authors: 
Bankole, T., West Virginia University
Jones, D. D., The Foxboro Company, Schneider Electric, Foxboro
Bhattacharyya, D., West Virginia University
Turton, R., West Virginia University
Zitney, S., National Energy Technology Laboratory, U.S. Department of Energy
Pre- and post-combustion carbon dioxide (CO2) capture from fossil fuel-fired power plants are potential approaches to mitigating build-up of CO2 concentration in the environment. However, state-of-the-art capture processes have high operating costs, mainly attributable to the energy penalties for regeneration and CO2 compression. In addition, the high penetration of renewable generators into the grid is expected to force advanced fossil energy plants with CO2 capture to follow the fluctuating load. Therefore, optimal scheduling of power plant dispatch and the COcapture rate are critical for maximizing plant profitability without sacrificing optimal control performance. While control of energy plants with carbon capture has been reported in the literature, there is little work that has investigated optimal scheduling of advanced power plants from the perspective of plant economics and controllability in the face of expected penalty/carbon tax scenarios.

It is anticipated that the CO2 capture targets will need to be satisfied over a period of time, denoted here as â??base timeâ??, which is expected to vary from region/country to region/country. The base time for CO2 capture may be several months to a year or more. Therefore, any discrepancy in the CO2 captured and the target during the previous time instances can be accounted for in the future time instances. This is unlike typical control objectives where the deviation from the set point in the past might be completely neglected or be considered with lower weights in the future. Thus inclusion of CO2 capture in the scheduling problem requires the solution of an optimization problem with a large horizon. One challenge for this class of problems is the large size of the online optimization problem. Efforts to reduce the horizon can lead to undesirable closed-loop characteristics such as bang-bang actuation or inventory creep. In addition, the input sequence for a reduced horizon formulation may be suboptimal when compared to an infinite horizon control formulation. Our work has evaluated the optimal scheduler profile for CO2 capture rate over time by considering three penalty/tax scenarios including the possibility of a cap-and-trade policy. The presentation will include a proof for the
stability of the developed scheduler algorithm and highlight its application to an integrated gasification combined cycle (IGCC) power plant with CO2 capture.