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Estimation of the failure probability of an integrated energy system based on the first order reliability method

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  • Fu, Xueqian
  • Guo, Qinglai
  • Sun, Hongbin
  • Zhang, Xiurong
  • Wang, Li

Abstract

In this paper, we investigate the impacts of intermittent renewable energy sources (RESs) and stochastic energy loads on the operation and uncertainties of an integrated energy system (IES). In our analysis, we use a first order reliability method (FORM) to estimate the failure probabilities, which are crucial for ensuring the reliability of the gas supply and surplus power absorption. The Hasofer Lind and Rackwitz Fiessler (HLRF) algorithm is introduced to solve the FORM optimization model while considering the stochastic behaviours and dependencies of multiple energy sources. A mathematical case is presented to demonstrate the use of the FORM in the estimation of failure probability, and the results are validated using the Latin hypercube sampling theories, including the Iman and Stein methods. The results of a failure probability analysis for an ideal IES are provided to illustrate the proposed technique. The failure probability can be used to improve IES operation and planning and ensure better reliability.

Suggested Citation

  • Fu, Xueqian & Guo, Qinglai & Sun, Hongbin & Zhang, Xiurong & Wang, Li, 2017. "Estimation of the failure probability of an integrated energy system based on the first order reliability method," Energy, Elsevier, vol. 134(C), pages 1068-1078.
  • Handle: RePEc:eee:energy:v:134:y:2017:i:c:p:1068-1078
    DOI: 10.1016/j.energy.2017.06.090
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    6. Wang, Can & Xie, Haipeng & Bie, Zhaohong & Li, Gengfeng & Yan, Chao, 2021. "Fast supply reliability evaluation of integrated power-gas system based on stochastic capacity network model and importance sampling," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    7. Chi, Lixun & Su, Huai & Zio, Enrico & Qadrdan, Meysam & Zhou, Jing & Zhang, Li & Fan, Lin & Yang, Zhaoming & Xie, Fei & Zuo, Lili & Zhang, Jinjun, 2023. "A systematic framework for the assessment of the reliability of energy supply in Integrated Energy Systems based on a quasi-steady-state model," Energy, Elsevier, vol. 263(PB).
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    11. Corrado lo Storto, 2019. "An SNA-DEA Prioritization Framework to Identify Critical Nodes of Gas Networks: The Case of the US Interstate Gas Infrastructure," Energies, MDPI, vol. 12(23), pages 1-18, December.
    12. Chi, Lixun & Su, Huai & Zio, Enrico & Qadrdan, Meysam & Li, Xueyi & Zhang, Li & Fan, Lin & Zhou, Jing & Yang, Zhaoming & Zhang, Jinjun, 2021. "Data-driven reliability assessment method of Integrated Energy Systems based on probabilistic deep learning and Gaussian mixture Model-Hidden Markov Model," Renewable Energy, Elsevier, vol. 174(C), pages 952-970.
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