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Real-time subsidy based robust scheduling of the integrated power and gas system

Author

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  • Shu, Kangan
  • Ai, Xiaomeng
  • Fang, Jiakun
  • Yao, Wei
  • Chen, Zhe
  • He, Haibo
  • Wen, Jinyu

Abstract

In this work, a real-time subsidy based robust scheduling method for the integrated gas and power system is proposed. Bi-directional energy conversion, including the power-to-gas and gas-fired generation, is operated via dynamic variant price signals. The gaming between the electrical power system and the natural gas system is formulated in the bi-level optimization. The upper-level problem minimizes the operational cost, in which the real-time subsidy for power-to-gas and gas-fired units is obtained. The lower-level problem maximizes the profit for the power-to-gas and gas-fired units, in which the transient gas flow is introduced. In addition, in order to counter the uncertainties brought on by wind power, a real-time subsidy update strategy based on robust optimization is proposed to stimulate the regulation capabilities of the power-to-gas and gas-fired units. This bi-level optimization is reformulated as a mixed-integer quadratic programming problem using the Karush-Kuhn-Tucker optimization conditions. Simulation results show that the real-time subsidy scheduling can make power-to-gas and gas-fired units follow the system operator’s preferences such as wind power accommodation, mitigation of unsupplied load, and relieving network congestion.

Suggested Citation

  • Shu, Kangan & Ai, Xiaomeng & Fang, Jiakun & Yao, Wei & Chen, Zhe & He, Haibo & Wen, Jinyu, 2019. "Real-time subsidy based robust scheduling of the integrated power and gas system," Applied Energy, Elsevier, vol. 236(C), pages 1158-1167.
    • Handle: RePEc:eee:appene:v:236:y:2019:i:c:p:1158-1167
    DOI: 10.1016/j.apenergy.2018.12.054
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    10. Jing Liu & Wei Sun & Gareth P. Harrison, 2019. "Optimal Low-Carbon Economic Environmental Dispatch of Hybrid Electricity-Natural Gas Energy Systems Considering P2G," Energies, MDPI, vol. 12(7), pages 1-17, April.

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