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Building a Sustainable Future: A Three-Stage Risk Management Model for High-Permeability Power Grid Engineering

Author

Listed:
  • Weijie Wu

    (Power Grid Planning Research Center of Guangdong Power Grid Corporation, Guangzhou 510080, China)

  • Dongwei Li

    (CEC Technical & Economic Consulting Center of Power Construction, Beijing 100053, China)

  • Hui Sun

    (Power Grid Planning Research Center of Guangdong Power Grid Corporation, Guangzhou 510080, China)

  • Yixin Li

    (Power Grid Planning Research Center of Guangdong Power Grid Corporation, Guangzhou 510080, China)

  • Yining Zhang

    (Power Grid Planning Research Center of Guangdong Power Grid Corporation, Guangzhou 510080, China)

  • Mingrui Zhao

    (CEC Technical & Economic Consulting Center of Power Construction, Beijing 100053, China)

Abstract

Under the background of carbon neutrality, it is important to construct a large number of high-permeability power grid engineering (HPGE) systems, since these can aid in addressing the security and stability challenges brought about by the high proportion of renewable energy. Construction and engineering frequently involve multiple risk considerations. In this study, we constructed a three-stage comprehensive risk management model of HPGE, which can help to overcome the issues of redundant risk indicators, imprecise risk assessment techniques, and irrational risk warning models in existing studies. First, we use the fuzzy Delphi model to identify the key risk indicators of HPGE. Then, the Bayesian best–worst method (Bayesian BWM) is adopted, as well as the measurement alternatives and ranking according to the compromise solution (MARCOS) approach, to evaluate the comprehensive risks of projects; these methods are proven to have more reliable weighting results and a larger sample separation through comparative analysis. Finally, we established an early warning risk model on the basis of the non-compensation principle, which can help prevent the issue of actual risk warning outcomes from being obscured by some indicators. The results show that the construction of the new power system and clean energy consumption policy are the key risk factors affecting HPGE. It was found that four projects are in an extremely high-risk warning state, five are in a relatively high-risk warning state, and one is in a medium-risk warning state. Therefore, it is necessary to strengthen the risk prevention of HPGE and to develop a reasonable closed-loop risk control mechanism.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:14:p:3439-:d:1433959
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    References listed on IDEAS

    as
    1. Rao Rao & Xingping Zhang & Zhiping Shi & Kaiyan Luo & Zhongfu Tan & Yifan Feng, 2014. "A Systematical Framework of Schedule Risk Management for Power Grid Engineering Projects’ Sustainable Development," Sustainability, MDPI, vol. 6(10), pages 1-30, October.
    2. Zhang, Yuanyuan & Zhao, Huiru & Li, Bingkang & Zhao, Yihang & Qi, Ze, 2022. "Research on credit rating and risk measurement of electricity retailers based on Bayesian Best Worst Method-Cloud Model and improved Credit Metrics model in China's power market," Energy, Elsevier, vol. 252(C).
    3. Xinping Wang & Cheng Zhang & Jun Deng & Chang Su & Zhenzhe Gao, 2022. "Analysis of Factors Influencing Miners’ Unsafe Behaviors in Intelligent Mines using a Novel Hybrid MCDM Model," IJERPH, MDPI, vol. 19(12), pages 1-30, June.
    4. Zhuola Zhang & Shiyuan Lin & Yingjin Ye & Zhao Xu & Yihang Zhao & Huiru Zhao & Jingqi Sun, 2022. "A Hybrid MCDM Model for Evaluating the Market-Oriented Business Regulatory Risk of Power Grid Enterprises Based on the Bayesian Best-Worst Method and MARCOS Approach," Energies, MDPI, vol. 15(9), pages 1-17, April.
    5. G.K. Koulinas & O.E. Demesouka & P.K. Marhavilas & A.P. Vavatsikos & D.E. Koulouriotis, 2019. "Risk Assessment Using Fuzzy TOPSIS and PRAT for Sustainable Engineering Projects," Sustainability, MDPI, vol. 11(3), pages 1-15, January.
    6. Jiao Wang, 2020. "Construction of Risk Evaluation Index System for Power Grid Engineering Cost by Applying WBS-RBS and Membership Degree Methods," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-9, August.
    7. 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.
    8. Norman Dalkey & Olaf Helmer, 1963. "An Experimental Application of the DELPHI Method to the Use of Experts," Management Science, INFORMS, vol. 9(3), pages 458-467, April.
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