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Reliability analysis of hybrid multi-carrier energy systems based on entropy-based Markov model

Author

Listed:
  • Xilin Zhao
  • Fei Liu
  • Bo Fu
  • Na Fang

Abstract

Various new technologies for conversion between different forms of energy promote the appearance of hybrid multi-carrier energy system. For the purpose of optimized dispatch of multi-carrier energy and the security requirement of energy system, the reliability of this kind of energy system needs to be discussed. This article proposes a method based on entropy-based Markov model to analyze the reliability of hybrid multi-carrier energy system. First, the method to obtain the reliability of individual energy carrier is discussed. Second, the characteristic of entropy-based Markov model is analyzed. The method is shown to be an effective technique to obtain the reliability of the whole multi-carrier energy system depending on the reliability of individual energy carrier. Then, the fusion process to obtain the reliability of whole multi-carrier energy system is described. The result indicates that the reliability of the whole system is the reliability synthesized of individual energy supply and can be treated as a factor for the optimized process of multi-carrier energy dispatch. The effectiveness of the method is demonstrated by some examples.

Suggested Citation

  • Xilin Zhao & Fei Liu & Bo Fu & Na Fang, 2016. "Reliability analysis of hybrid multi-carrier energy systems based on entropy-based Markov model," Journal of Risk and Reliability, , vol. 230(6), pages 561-569, December.
    • Handle: RePEc:sae:risrel:v:230:y:2016:i:6:p:561-569
    DOI: 10.1177/1748006X16663056
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    References listed on IDEAS

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    1. Niknam, Taher & Azizipanah-Abarghooee, Rasoul & Roosta, Alireza & Amiri, Babak, 2012. "A new multi-objective reserve constrained combined heat and power dynamic economic emission dispatch," Energy, Elsevier, vol. 42(1), pages 530-545.
    2. Koeppel, Gaudenz & Andersson, Göran, 2009. "Reliability modeling of multi-carrier energy systems," Energy, Elsevier, vol. 34(3), pages 235-244.
    3. A. M. Elaiw & X. Xia & A. M. Shehata, 2013. "Combined Heat and Power Dynamic Economic Dispatch with Emission Limitations Using Hybrid DE-SQP Method," Abstract and Applied Analysis, Hindawi, vol. 2013, pages 1-10, November.
    4. Zong Woo Geem, 2013. "Economic Dispatch Using Parameter-Setting-Free Harmony Search," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-5, May.
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