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A Comprehensive Evaluation Method and Strengthening Measures for AC/DC Hybrid Power Grids

Author

Listed:
  • Junli Zhang

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Guoteng Wang

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Zheng Xu

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Zheren Zhang

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

Abstract

Due to the complex operation characteristics of AC/DC hybrid power grids, it is a great challenge to comprehensively evaluate their stability and formulate appropriate strengthening schemes for them. To address this challenge, the following studies are carried out in this paper. First, an evaluation system including six indicators is established for AC/DC hybrid power grids. Next, aiming at the problems that may be revealed by the comprehensive evaluation, strengthening measures that can be utilized are introduced. Then, a comprehensive evaluation method for AC/DC hybrid power grids and their potential strengthening schemes is proposed. This method can deal with three issues, including normalization of the indicators, weighting of the indicators, and the trade-off of technology and cost. Finally, in the case study of the Qujing Power Grid, the main problems faced by regional power grids are pointed out, and four feasible strengthening schemes are formulated and evaluated.

Suggested Citation

  • Junli Zhang & Guoteng Wang & Zheng Xu & Zheren Zhang, 2022. "A Comprehensive Evaluation Method and Strengthening Measures for AC/DC Hybrid Power Grids," Energies, MDPI, vol. 15(12), pages 1-20, June.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:12:p:4432-:d:841606
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    References listed on IDEAS

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    1. Dahai You, A. & QingQian Chen, B. & Xianggen Yin, C. & Bo Wang, D., 2011. "A study of Electrical Security Risk Assessment System based on Electricity Regulation," Energy Policy, Elsevier, vol. 39(4), pages 2062-2074, April.
    2. Rezaei, Jafar, 2016. "Best-worst multi-criteria decision-making method: Some properties and a linear model," Omega, Elsevier, vol. 64(C), pages 126-130.
    3. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
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