Modeling the operational flexibility of natural gas combined cycle power plants coupled with flexible carbon capture and storage via solvent storage and flexible regeneration. (July 2022) - Cheng, Fangwei; Patankar, Neha; Chakrabarti, Sambuddha; Jenkins, Jesse D.
Highlights: We present an integrated framework that captures plant-level and grid-level values of flexible CCS. Linear relaxation of integer clustering unit commitment method offers significant time reduction with minor errors. Flexible CCS reduces the system operating cost by displacing high marginal units during peak demand. Flexible CCS may be more favorable in the future grids with high variable renewable penetration. Abstract: In electricity systems with high shares of variable renewable energy resources, the capability to flexible alter power output can increase the economic value of natural gas combined cycle (NGCC) power plants equipped with carbon capture and sequestration (CCS) and enhance their competitiveness as firm low-carbon resources. Here we examine NGCC power plants w/CCS (NGCC-CCS) coupled with solvent storage to enable flexible operation. We present a modular and detailed modeling formulation to represent these systems in a computationally efficient and accurate manner and to evaluate the operating patterns and system value of flexible CCS designs. The proposed framework breaks down NGCC-CCS plants into major subcomponents and uses linear constraint formulations to enforce energy and mass balances. In addition, thermal power plants are subjected to unit commitment (UC) constraints that are generally time-consuming to solve via conventional methods, which use binary decision variables for start-up and shut-down decisions. We thereby investigate whether the linear relaxation of discrete UC decision variables coupled with a generator clustering method are applicable to model flexible CCS subcomponents. Finally, we integrate this novel flexible CCS formulation into a power system unit commitment and economic dispatch model to present a case study that shows the hourly operating patterns of NGCC-CCS subcomponents and impacts on power system environmental and economic performance. As compared to a conventional binary UC formulation, our results show that linear relaxation of a generator clustering formulation has much faster runtime (18–527 times faster), with errors of 0.01%-3.4% across all the evaluated metrics. The operating patterns and system performance suggest our modeling framework can accurately and tractably capture both plant-level and system-level outcomes. Finally, our results demonstrate that flexible NGCC-CCS systems decrease power system operating costs by increasing power output during peak demand periods to displace higher marginal cost units. We also demonstrate that the system-level benefits provided by flexible operation of NGCC-CCS plants will be increasingly valuable to the future grids with high penetration of variable renewable resources.