American Journal of Environmental and Resource Economics

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Operational Risk Identification of Electric Power Market Management Committee Based on Intuitionistic Fuzzy FMEA and TOPSIS-GRPM Methods

Received: May 14, 2019    Accepted: Jun. 13, 2019    Published: Jul. 26, 2019
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Abstract

With the new round of power industry reform in China, the Power Market Management Committee (PMMC) came into being as an autonomous deliberation and coordination body. PMMC plays a bridge role in power market operation, but its operating mechanism is still in the exploratory stage. Research on how to effectively play the functional role in the power market and avoid the effectiveness of the risk is still blank. In order to scientifically identify and evaluate the operational risks of the PMMC and provide guidance and reference for its operation in the electricity market, the article focuses on its responsibilities and procedures, and benchmarks with similar institutions at home and abroad. The traditional FMEA method is applied to analyze the potential risk causes and consequences of PMMC operation, and nine potential risk factors are extracted, then the initial weights of the risk factors were determined by combining the subjective and objective weighting methods with the intuitionistic fuzzy set FMEA method, then the TOPSIS-GRPM method is used to calculate the gray correlation projection closeness, and the final weight of the risk factor is determined. From the evaluation results, it can be seen that the risk of members' composition, professional ability and authority and responsibility allocation are of high level, and need to be focused on prevention and control. Finally, effective measures to avoid and prevent PMMC are put forward to provide reference for the safe and efficient operation of PMMC in China.

DOI 10.11648/j.ajere.20190403.12
Published in American Journal of Environmental and Resource Economics ( Volume 4, Issue 3, September 2019 )
Page(s) 96-103
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Operational Risk, Risk Model, PMMC, Intuitionistic Fuzzy FMEA Method, TOPSIS-GRPM

References
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  • APA Style

    Jun Dong, Dongxue Wang, Xihao Dou, Dongran Liu, Shilin Nie, et al. (2019). Operational Risk Identification of Electric Power Market Management Committee Based on Intuitionistic Fuzzy FMEA and TOPSIS-GRPM Methods. American Journal of Environmental and Resource Economics, 4(3), 96-103. https://doi.org/10.11648/j.ajere.20190403.12

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    ACS Style

    Jun Dong; Dongxue Wang; Xihao Dou; Dongran Liu; Shilin Nie, et al. Operational Risk Identification of Electric Power Market Management Committee Based on Intuitionistic Fuzzy FMEA and TOPSIS-GRPM Methods. Am. J. Environ. Resour. Econ. 2019, 4(3), 96-103. doi: 10.11648/j.ajere.20190403.12

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    AMA Style

    Jun Dong, Dongxue Wang, Xihao Dou, Dongran Liu, Shilin Nie, et al. Operational Risk Identification of Electric Power Market Management Committee Based on Intuitionistic Fuzzy FMEA and TOPSIS-GRPM Methods. Am J Environ Resour Econ. 2019;4(3):96-103. doi: 10.11648/j.ajere.20190403.12

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  • @article{10.11648/j.ajere.20190403.12,
      author = {Jun Dong and Dongxue Wang and Xihao Dou and Dongran Liu and Shilin Nie and Linpeng Nie},
      title = {Operational Risk Identification of Electric Power Market Management Committee Based on Intuitionistic Fuzzy FMEA and TOPSIS-GRPM Methods},
      journal = {American Journal of Environmental and Resource Economics},
      volume = {4},
      number = {3},
      pages = {96-103},
      doi = {10.11648/j.ajere.20190403.12},
      url = {https://doi.org/10.11648/j.ajere.20190403.12},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ajere.20190403.12},
      abstract = {With the new round of power industry reform in China, the Power Market Management Committee (PMMC) came into being as an autonomous deliberation and coordination body. PMMC plays a bridge role in power market operation, but its operating mechanism is still in the exploratory stage. Research on how to effectively play the functional role in the power market and avoid the effectiveness of the risk is still blank. In order to scientifically identify and evaluate the operational risks of the PMMC and provide guidance and reference for its operation in the electricity market, the article focuses on its responsibilities and procedures, and benchmarks with similar institutions at home and abroad. The traditional FMEA method is applied to analyze the potential risk causes and consequences of PMMC operation, and nine potential risk factors are extracted, then the initial weights of the risk factors were determined by combining the subjective and objective weighting methods with the intuitionistic fuzzy set FMEA method, then the TOPSIS-GRPM method is used to calculate the gray correlation projection closeness, and the final weight of the risk factor is determined. From the evaluation results, it can be seen that the risk of members' composition, professional ability and authority and responsibility allocation are of high level, and need to be focused on prevention and control. Finally, effective measures to avoid and prevent PMMC are put forward to provide reference for the safe and efficient operation of PMMC in China.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - Operational Risk Identification of Electric Power Market Management Committee Based on Intuitionistic Fuzzy FMEA and TOPSIS-GRPM Methods
    AU  - Jun Dong
    AU  - Dongxue Wang
    AU  - Xihao Dou
    AU  - Dongran Liu
    AU  - Shilin Nie
    AU  - Linpeng Nie
    Y1  - 2019/07/26
    PY  - 2019
    N1  - https://doi.org/10.11648/j.ajere.20190403.12
    DO  - 10.11648/j.ajere.20190403.12
    T2  - American Journal of Environmental and Resource Economics
    JF  - American Journal of Environmental and Resource Economics
    JO  - American Journal of Environmental and Resource Economics
    SP  - 96
    EP  - 103
    PB  - Science Publishing Group
    SN  - 2578-787X
    UR  - https://doi.org/10.11648/j.ajere.20190403.12
    AB  - With the new round of power industry reform in China, the Power Market Management Committee (PMMC) came into being as an autonomous deliberation and coordination body. PMMC plays a bridge role in power market operation, but its operating mechanism is still in the exploratory stage. Research on how to effectively play the functional role in the power market and avoid the effectiveness of the risk is still blank. In order to scientifically identify and evaluate the operational risks of the PMMC and provide guidance and reference for its operation in the electricity market, the article focuses on its responsibilities and procedures, and benchmarks with similar institutions at home and abroad. The traditional FMEA method is applied to analyze the potential risk causes and consequences of PMMC operation, and nine potential risk factors are extracted, then the initial weights of the risk factors were determined by combining the subjective and objective weighting methods with the intuitionistic fuzzy set FMEA method, then the TOPSIS-GRPM method is used to calculate the gray correlation projection closeness, and the final weight of the risk factor is determined. From the evaluation results, it can be seen that the risk of members' composition, professional ability and authority and responsibility allocation are of high level, and need to be focused on prevention and control. Finally, effective measures to avoid and prevent PMMC are put forward to provide reference for the safe and efficient operation of PMMC in China.
    VL  - 4
    IS  - 3
    ER  - 

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Author Information
  • School of Economics and Management, North China Electric Power University, Beijing, China

  • School of Economics and Management, North China Electric Power University, Beijing, China

  • School of Economics and Management, North China Electric Power University, Beijing, China

  • School of Economics and Management, North China Electric Power University, Beijing, China

  • School of Economics and Management, North China Electric Power University, Beijing, China

  • School of Economics and Management, North China Electric Power University, Beijing, China

  • Section