(544d) Optimization of a Flexible Carbon Capture-Equipped Power Plant Integrated with Lime-Based Direct Air Capture Under Time-Varying Electricity Prices

Optimization of a flexible carbon capture-equipped power plant integrated with lime-based direct air capture under time-varying electricity prices

Carbon capture and storage (CCS) equipped fossil fuel power plants on the supply-side and direct air capture (DAC) technologies on the demand side can address the dual challenge of lower carbon emissions while providing grid flexibility. We consider the optimization of a novel process that combines three main technologies: calcium looping, membrane and cryogenic separation, and lime-based DAC. In this case the process is designed to incorporate flue gas from a conventional natural gas combined cycle (NGCC) plant. The calcium loop separates CO₂ from the flue gas, with CaO being the chemical sorbent. It also produces CaO at a rate equal to a fresh CaCO₃ feed, which captures CO₂ from the atmosphere in the DAC unit. Calciner off-gas is fed to electrically-driven membrane and cryogenic separation units to produce high purity CO₂ suitable for sequestration. Process units (DAC, calciner and separation system) can operate continuously to handle the feed CaCO₃ even at zero NGCC plant loadings, meaning that the process can operate flexibly in response to variations in the flue gas feed.

In this presentation, we will discuss the development and use of a mixed-integer nonlinear programming (MINLP) framework to optimize the design and scheduling of the proposed power plant concept under time-varying electricity prices. The MINLP model incorporates the following features: a) surrogate models of the individual unit operations (e.g. membrane, calcium looping system) based on detailed Aspen plus simulations in conjunction with adaptive sampling approaches, b) detailed costing models that incorporate scaling of various unit operations and c) use of representative periods (e.g. days) to model plant operations at an hourly resolution. We use the developed model to assess the optimal design and scheduling of the process with respect to different market scenarios (annual electricity price profiles, carbon tax and natural gas prices available) based on input provided by other research groups part of the ARPA-E FLECCS program [1,2]. Preliminary results reveal that the optimal process consists of near-steady and high-capacity utilization of the calciner, with the hourly distribution of the produced lime between carbonator (for flue gas CO₂ capture) and lime DAC being a function of the carbon price imposed and hourly electricity prices. In general, more lime is sent to the DAC when power plant is operating at low loading (low electricity prices) as compared to high loading (high electricity prices) and this spread increases with increasing carbon price. Overall, our analysis suggests that positive NPV designs are achievable, with higher profitability in higher carbon price scenarios, driven primarily by revenues from CO₂ capture from the DAC process.

[1] Cohen, Stuart; Durvasulu, Venkat (2021): NREL Price Series Developed for the ARPA-E FLECCS Program. National Renewable Energy Laboratory. 10.7799/1838046

[2] Jenkins, D. Jesse; Chakrabarti, Sambuddha (2021): Summary Report of the GenX and PowerGenome runs for generating Price Series (for ARPA-E FLECCS Project). Zenodo. 10.5281/ZENODO.5765798