(15a) Long-Term Multi-Stage Retrofit Planning of Carbon Negative Ngcc Plants with Direct Air Capture Under Carbon Market Uncertainty

As the leading power generation technique in the United States [1], natural gas combined cycle (NGCC) faces imminent challenges in the changing energy landscape: Even if its carbon footprint is relatively low, volatile electricity demands [2, 3], caused by the increasing renewable energy penetration, along with the stringent emission constraints, will make existing NGCC plants a losing venture in the coming decades [4]. Therefore, it is imperative to retrofit existing NGCC plants with advanced carbon capture technologies to sustain their significant generation capacity and ensure their environmental compliance.

The GaTech FLECCS team has proposed a novel multi-stage retrofit design to existing NGCCs to achieve carbon negativity and system flexibility without compromising dispatch capacity. This approach combines both post-combustion carbon capture (PCC) and direct air capture (DAC), utilizing advanced separation techniques [5] for efficient CO2 removal. The design features a novel heat integration strategy for versatile low-pressure steam utilization, enabling optimized responses to fluctuating electricity prices and thus avoiding frequent system start-ups and shutdowns. Moreover, the phased retrofit approach allows the plant owners to incrementally enhance the carbon capture capacity, mitigating technological risks and offering adaptability in policy compliance. However, the long-term viability of DAC, given its higher costs due to ambient CO2 dilution, is closely tied to the evolving carbon market, which is impacted by various macroeconomic, technology and policy-related factors and thus highly uncertain [6]. This underscores the pressing need for detailed modeling to assess the financial feasibility of the proposed design under different carbon market trajectories.

In this work, we model the proposed multi-stage NGCC-PCC-DAC retrofit and co-optimize the design and operation decisions in various future energy scenarios over a 20-year horizon. We consider three retrofit stages: NGCC with DAC, NGCC with DAC and half PCC (50% capture capacity), and NGCC with DAC and full PCC. The stage progression leads to increasing carbon capture capabilities and is supported with detailed unit design and simulation. In addition, all stages allow additional optional units including the electric heater and the package boiler for extra steam generation. For each year within the horizon, the design decisions determine the capital investment and include (1) whether to progress into the next retrofit stage, and (2) if so, sizing of the DAC and optional units. The operational decisions reflect the system profitability for a given energy demand profile and include hourly operations of each submodule within the year. The overall multi-stage, multi-scale framework was represented with disjunctive programming techniques [7]. The energy scenarios are composed of multiple baseline CO2 price trajectories and their associated high-resolution electricity price signals generated from GenX [8]. Finally, we use representative weeks to effectively reduce the time domain and keep the model tractable, and we apply a customized backtracking algorithm to solve the corresponding MILP problems efficiently.

References

[1] U.S. Energy Information Administration, "Electric Power Annual," 19 10 2023. [Online]. Available: https://www.eia.gov/electricity/annual/.
[2] J. D. Jenkins, S. Chakrabarti, F. Cheng and N. Patankar, "Summary Report of the GenX and PowerGenome runs for generating Price Series (for ARPA-E FLECCS Project)," 2021. [Online]. Available: https://zenodo.org/records/5765798.
[3] S. Cohen and V. Durvasulu, "NREL Price Series Developed for the ARPA-E FLECCS Program," 23 12 2021. [Online]. Available: https://doi.org/10.7799/1838046.
[4] P. Cheng, D. M. Thierry, H. Hendrix, K. D. Dombrowski, D. J. Sachde, M. J. Realff and J. K. Scott, "Modeling and optimization of carbon-negative NGCC plant enabled by modular direct air capture," Applied Energy, p. 121076, 2023.
[5] A. R. Sujan, S. H. Pang, G. Zhu, C. W. Jones and R. P. Lively, "Direct CO2 Capture from Air using Poly(ethylenimine)-Loaded Polymer/Silica Fiber Sorbents," ACS Sustainable Chemistry & Engineering, pp. 5264-5273, 2019.
[6] BloombergNEF, "Long-Term Carbon Offsets Outlook 2023," 2023. [Online]. Available: https://spotlight.bloomberg.com/story/longtermcarbonoffsetsoutlook2023/.
[7] E. Balas, Disjunctive Programming, Springer, 2018.
[8] MIT Energy Initiative and Princeton University ZERO lab, "GenX: a configurable power system capacity expansion model for studying low-carbon energy futures," [Online]. Available: https://github.com/GenXProject/GenX.