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Probabilistic energy flow and risk assessment of Electricity–Gas systems considering the thermodynamic process

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  • Bao, Shiyuan
  • Yang, Zhifang
  • Yu, Juan
  • Dai, Wei
  • Guo, Lin
  • Yu, Hongxin

Abstract

The existing analyses of the electricity–gas systems generally do not regard the nodal gas temperature as a state variable. However, the temperature variations caused by the thermodynamic process are important because of the following two reasons: 1) gas temperature influences the pressure and gas flow; 2) gas temperature is an important indicator for hydrate formation in gas networks, which greatly jeopardizes the gas transmission. We herein propose a probabilistic energy flow method considering the thermodynamic process in gas networks. To build the energy flow model, the algebraic pipeline flow model under the non-isothermal condition is derived according to a set of partial differential equations reflecting the thermodynamic process. The models of pressure-regulating stations and compression stations considering the thermodynamic processes are presented in an electricity–gas analysis for the first time. Risk indices are proposed to quantify the risks of hydrate formation and state variables that exceed the limits. The simulation results of two test cases demonstrate the effectiveness of the proposed method.

Suggested Citation

  • Bao, Shiyuan & Yang, Zhifang & Yu, Juan & Dai, Wei & Guo, Lin & Yu, Hongxin, 2019. "Probabilistic energy flow and risk assessment of Electricity–Gas systems considering the thermodynamic process," Energy, Elsevier, vol. 189(C).
    • Handle: RePEc:eee:energy:v:189:y:2019:i:c:s0360544219319589
    DOI: 10.1016/j.energy.2019.116263
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    References listed on IDEAS

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    1. Pambour, Kwabena Addo & Cakir Erdener, Burcin & Bolado-Lavin, Ricardo & Dijkema, Gerard P.J., 2017. "SAInt – A novel quasi-dynamic model for assessing security of supply in coupled gas and electricity transmission networks," Applied Energy, Elsevier, vol. 203(C), pages 829-857.
    2. Chaczykowski, Maciej & Zarodkiewicz, Paweł, 2017. "Simulation of natural gas quality distribution for pipeline systems," Energy, Elsevier, vol. 134(C), pages 681-698.
    3. Sheikhi, Aras & Bahrami, Shahab & Ranjbar, Ali Mohammad, 2015. "An autonomous demand response program for electricity and natural gas networks in smart energy hubs," Energy, Elsevier, vol. 89(C), pages 490-499.
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    Cited by:

    1. Sayed, Ahmed Rabee & Wang, Cheng & Chen, Sheng & Shang, Ce & Bi, Tianshu, 2021. "Distributionally robust day-ahead operation of power systems with two-stage gas contracting," Energy, Elsevier, vol. 231(C).
    2. Chen, Sheng & Sun, Guoqiang & Wei, Zhinong & Wang, Dan, 2020. "Dynamic pricing in electricity and natural gas distribution networks: An EPEC model," Energy, Elsevier, vol. 207(C).
    3. Huang, Gang & Wang, Jianhui & Wang, Cheng & Guo, Chuangxin, 2021. "Cascading imbalance in coupled gas-electric energy systems," Energy, Elsevier, vol. 231(C).

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