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Optimal design and operations of a flexible oxyfuel natural gas plant

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  • Teichgraeber, Holger
  • Brodrick, Philip G.
  • Brandt, Adam R.

Abstract

We co-optimize the design and operations of a flexible semi-closed oxygen-combustion combined cycle (SCOC-CC) carbon capture plant under time-varying electricity prices. The system consists of a cryogenic air separation unit, liquid oxygen storage, a gas turbine, a heat-recovery steam generator, and a steam turbine. The gas turbine is modeled allowing part-load operation. Computational optimization is used to maximize net present value (NPV) in order to examine the potential benefits achievable through upfront investments in increased flexibility (i.e., allowing price arbitrage between times of low and high price). Case studies of Germany and California are examined. Flexible SCOC-CC systems are not profitable in either region under current electricity prices. With electricity prices ≈2 times current prices, we find systems with positive NPVs. Oxygen storage is used in days with extreme price variability. Optimal designs favor constant operation, without over- or under-sizing system components and without additional oxygen storage. Sensitivity analyses show that external factors such as mean electricity price (± 200%), natural gas price (± 150%), and nominal discount rate (± 50%) have the strongest effect on NPV. Electricity price variability, which is thought to increase with increased penetration of renewables, does not strongly impact system design and profitability.

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  • Teichgraeber, Holger & Brodrick, Philip G. & Brandt, Adam R., 2017. "Optimal design and operations of a flexible oxyfuel natural gas plant," Energy, Elsevier, vol. 141(C), pages 506-518.
    • Handle: RePEc:eee:energy:v:141:y:2017:i:c:p:506-518
    DOI: 10.1016/j.energy.2017.09.087
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    4. Teichgraeber, Holger & Lindenmeyer, Constantin P. & Baumgärtner, Nils & Kotzur, Leander & Stolten, Detlef & Robinius, Martin & Bardow, André & Brandt, Adam R., 2020. "Extreme events in time series aggregation: A case study for optimal residential energy supply systems," Applied Energy, Elsevier, vol. 275(C).
    5. Maximilian Hoffmann & Leander Kotzur & Detlef Stolten & Martin Robinius, 2020. "A Review on Time Series Aggregation Methods for Energy System Models," Energies, MDPI, vol. 13(3), pages 1-61, February.
    6. Teichgraeber, Holger & Küpper, Lucas Elias & Brandt, Adam R., 2021. "Designing reliable future energy systems by iteratively including extreme periods in time-series aggregation," Applied Energy, Elsevier, vol. 304(C).
    7. Brodrick, Philip G. & Brandt, Adam R. & Durlofsky, Louis J., 2018. "Optimal design and operation of integrated solar combined cycles under emissions intensity constraints," Applied Energy, Elsevier, vol. 226(C), pages 979-990.
    8. Teichgraeber, Holger & Brandt, Adam R., 2022. "Time-series aggregation for the optimization of energy systems: Goals, challenges, approaches, and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    9. Sakalis, George N. & Frangopoulos, Christos A., 2018. "Intertemporal optimization of synthesis, design and operation of integrated energy systems of ships: General method and application on a system with Diesel main engines," Applied Energy, Elsevier, vol. 226(C), pages 991-1008.
    10. Kuepper, Lucas Elias & Teichgraeber, Holger & Baumgärtner, Nils & Bardow, André & Brandt, Adam R., 2022. "Wind data introduce error in time-series reduction for capacity expansion modelling," Energy, Elsevier, vol. 256(C).

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