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Shale-gas scheduling for natural-gas supply in electric power production

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  • Knudsen, Brage Rugstad
  • Whitson, Curtis H.
  • Foss, Bjarne

Abstract

This paper describes a novel integration of shale-gas supply in geographical proximity to natural-gas power production. Shale-gas reservoirs hold special properties that make them particularly suited for intermittent shut-in based production schemes. The proposed scheme argues that shale-gas reservoirs can be used to shift storage of gas used for meeting varying demands, from separate underground storage units operated by local distribution companies to the gas producers themselves. Based on this property, we present an economical attractive option for generating companies to increase their use of firm gas–supply contracts to the natural-gas power plants in order to secure a sufficient gas supply. The shale-well scheduling is formulated as profit-maximization model for well operators, in which we seek to include their main operational challenges, while preserving an economic incentive for the operators to adopt the proposed scheme. The resulting large-scale mixed integer linear program is solved by a Lagrangian relaxation scheme, with a receding horizon strategy implemented to handle operational uncertainties. We present the proposed optimization framework by illustrative case studies. The numerical results show a significant economic potential for the shale-well operators, and a viable approach for generating companies to secure a firm gas supply for meeting varying seasonal electricity demands.

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  • Knudsen, Brage Rugstad & Whitson, Curtis H. & Foss, Bjarne, 2014. "Shale-gas scheduling for natural-gas supply in electric power production," Energy, Elsevier, vol. 78(C), pages 165-182.
    • Handle: RePEc:eee:energy:v:78:y:2014:i:c:p:165-182
    DOI: 10.1016/j.energy.2014.09.076
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    References listed on IDEAS

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    3. Alexopoulos, Thomas A., 2017. "The growing importance of natural gas as a predictor for retail electricity prices in US," Energy, Elsevier, vol. 137(C), pages 219-233.
    4. Hernán Gómez-Villarreal & Miguel Carrión & Ruth Domínguez, 2019. "Optimal Management of Combined-Cycle Gas Units with Gas Storage under Uncertainty," Energies, MDPI, vol. 13(1), pages 1-29, December.
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    6. Tan, Siah Hong & Barton, Paul I., 2017. "Optimal shale oil and gas investments in the United States," Energy, Elsevier, vol. 141(C), pages 398-422.
    7. Hong, Bingyuan & Li, Xiaoping & Song, Shangfei & Chen, Shilin & Zhao, Changlong & Gong, Jing, 2020. "Optimal planning and modular infrastructure dynamic allocation for shale gas production," Applied Energy, Elsevier, vol. 261(C).
    8. Knudsen, Brage Rugstad & Foss, Bjarne, 2017. "Shale-gas wells as virtual storage for supporting intermittent renewables," Energy Policy, Elsevier, vol. 102(C), pages 142-144.
    9. Jiang, Yongdong & Luo, Yahuang & Lu, Yiyu & Qin, Chao & Liu, Hui, 2016. "Effects of supercritical CO2 treatment time, pressure, and temperature on microstructure of shale," Energy, Elsevier, vol. 97(C), pages 173-181.
    10. Tunstall, Thomas, 2015. "Iterative Bass Model forecasts for unconventional oil production in the Eagle Ford Shale," Energy, Elsevier, vol. 93(P1), pages 580-588.
    11. Tan, Siah Hong & Barton, Paul I., 2015. "Optimal dynamic allocation of mobile plants to monetize associated or stranded natural gas, part I: Bakken shale play case study," Energy, Elsevier, vol. 93(P2), pages 1581-1594.
    12. Liu, Yuan & He, Li & Shen, Jing, 2017. "Optimization-based provincial hybrid renewable and non-renewable energy planning – A case study of Shanxi, China," Energy, Elsevier, vol. 128(C), pages 839-856.

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