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Risk Evaluation of Electric Power Grid Investment in China Employing a Hybrid Novel MCDM Method

Author

Listed:
  • Yana Duan

    (National Electric Power Grid Inner Mongolia Eastern Electric Power Co., Ltd., Economic and Technological Research Institute, Hohhot 010000, China)

  • Yang Sun

    (National Electric Power Grid Inner Mongolia Eastern Electric Power Co., Ltd., Economic and Technological Research Institute, Hohhot 010000, China)

  • Yu Zhang

    (National Electric Power Grid Inner Mongolia Eastern Electric Power Co., Ltd., Economic and Technological Research Institute, Hohhot 010000, China)

  • Xiaoqi Fan

    (National Electric Power Grid Inner Mongolia Eastern Electric Power Co., Ltd., Economic and Technological Research Institute, Hohhot 010000, China)

  • Qinghuan Dong

    (National Electric Power Grid Inner Mongolia Eastern Electric Power Co., Ltd., Economic and Technological Research Institute, Hohhot 010000, China)

  • Sen Guo

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

Abstract

Socio-economic development is undergoing changes in China, such as the recently proposed carbon peak and carbon neutral targets, new infrastructure development strategy and the Coronavirus disease 2019 (COVID-19) pandemic. Meanwhile, the new-round marketization reform of the electricity industry has been ongoing in China since 2015. Therefore, it is urgent to evaluate the risk of electric power grid investment in China under new socio-economic development situation, which can help the investors manage risk and reduce risk loss. In this paper, a hybrid novel multi-criteria decision making (MCDM) method combining the latest group MCDM method, namely, Bayesian best–worst method (BBWM) and improved matter-element extension model (IMEEM) is proposed for risk evaluation of electric power grid investment in China under new socio-economic development situation. The BBWM is used for the weights’ determination of electric power grid investment risk criteria, and the IMEEM is employed to rank risk grade of electric power grid investment. The risk evaluation index system of electric power grid investment is built, including economic, social, environmental, technical and marketable risks. The risk of electric power grid investment under new socio-economic development situation in Inner Mongolia Autonomous Region of China is empirically evaluated by using the proposed MCDM method, and the results indicate that it belongs to “Medium” grade, but closer to “High” grade. The main contributions of this paper include: (1) it proposes a hybrid novel MCDM method combining the BBWM and IMEEM for risk evaluation of electric power grid investment; and (2) it provides a new view for risk evaluation of electric power grid investment including economic, social, environmental, technical and marketable risks. The proposed hybrid novel MCDM method for the risk evaluation of electric power grid investment is effective and practical.

Suggested Citation

  • Yana Duan & Yang Sun & Yu Zhang & Xiaoqi Fan & Qinghuan Dong & Sen Guo, 2021. "Risk Evaluation of Electric Power Grid Investment in China Employing a Hybrid Novel MCDM Method," Mathematics, MDPI, vol. 9(5), pages 1-22, February.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:5:p:473-:d:505594
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    Cited by:

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    2. Changzheng Gao & Xiuna Wang & Dongwei Li & Chao Han & Weiyang You & Yihang Zhao, 2023. "A Novel Hybrid Power-Grid Investment Optimization Model with Collaborative Consideration of Risk and Benefit," Energies, MDPI, vol. 16(20), pages 1-23, October.
    3. Weijie Wu & Dongwei Li & Hui Sun & Yixin Li & Yining Zhang & Mingrui Zhao, 2024. "Building a Sustainable Future: A Three-Stage Risk Management Model for High-Permeability Power Grid Engineering," Energies, MDPI, vol. 17(14), pages 1-23, July.

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