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Critical Lines Identification for Skeleton-Network of Power Systems under Extreme Weather Conditions Based on the Modified VIKOR Method

Author

Listed:
  • Chang Han

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

  • Yuxuan Zhao

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

  • Zhenzhi Lin

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

  • Yi Ding

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

  • Li Yang

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

  • Guanqiang Lin

    (Electric Power Dispatching and Control Center, Huizhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Huizhou 516000, China)

  • Tianwen Mo

    (Electric Power Dispatching and Control Center, Huizhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Huizhou 516000, China)

  • Xiaojun Ye

    (Electric Power Dispatching and Control Center, Huizhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Huizhou 516000, China)

Abstract

Identifying and preferentially reinforcing critical lines for skeleton-network of power systems is significant in improving the secure and stable operation of power systems under extreme weather conditions. Under this background, in this paper, six indexes are first presented for identifying critical lines for skeleton-network with the power elements’ parameters and the impact of extreme weather conditions, the network topology and the operation state of power systems considered. Then, the modified Vise Kriterijumska Optimizacija I Kompromisno Resenje in Serbian (VIKOR) method, in which the synthetic weights of indexes determined by the combination weighting method are adopted, is utilized to identify the importance degrees of lines in a given power system. Both the overall performance and the outstanding individual performance of lines are considered, which is beneficial for the critical lines identification for skeleton-network. Finally, the proposed multi-indexes and methods are applied to part of the actual Guangdong power system in China. The numerical results are compared with those obtained by single-attribute and multi-attribute evaluation methods and other evaluation methods.

Suggested Citation

  • Chang Han & Yuxuan Zhao & Zhenzhi Lin & Yi Ding & Li Yang & Guanqiang Lin & Tianwen Mo & Xiaojun Ye, 2018. "Critical Lines Identification for Skeleton-Network of Power Systems under Extreme Weather Conditions Based on the Modified VIKOR Method," Energies, MDPI, vol. 11(6), pages 1-18, May.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:6:p:1355-:d:149073
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    References listed on IDEAS

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    1. Jun Dong & Rong Li & Hui Huang, 2018. "Performance Evaluation of Residential Demand Response Based on a Modified Fuzzy VIKOR and Scalable Computing Method," Energies, MDPI, vol. 11(5), pages 1-27, April.
    2. R. Kinney & P. Crucitti & R. Albert & V. Latora, 2005. "Modeling cascading failures in the North American power grid," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 46(1), pages 101-107, July.
    3. Jianxi Gao & Xueming Liu & Daqing Li & Shlomo Havlin, 2015. "Recent Progress on the Resilience of Complex Networks," Energies, MDPI, vol. 8(10), pages 1-24, October.
    4. Ziqi Wang & Jinghan He & Alexandru Nechifor & Dahai Zhang & Peter Crossley, 2017. "Identification of Critical Transmission Lines in Complex Power Networks," Energies, MDPI, vol. 10(9), pages 1-19, August.
    5. Nayyar Hussain Mirjat & Mohammad Aslam Uqaili & Khanji Harijan & Mohd Wazir Mustafa & Md. Mizanur Rahman & M. Waris Ali Khan, 2018. "Multi-Criteria Analysis of Electricity Generation Scenarios for Sustainable Energy Planning in Pakistan," Energies, MDPI, vol. 11(4), pages 1-33, March.
    6. Huiru Zhao & Nana Li, 2016. "Optimal Siting of Charging Stations for Electric Vehicles Based on Fuzzy Delphi and Hybrid Multi-Criteria Decision Making Approaches from an Extended Sustainability Perspective," Energies, MDPI, vol. 9(4), pages 1-22, April.
    7. Lin He & Chang-Ling Li & Qing-Yun Nie & Yan Men & Hai Shao & Jiang Zhu, 2017. "Core Abilities Evaluation Index System Exploration and Empirical Study on Distributed PV-Generation Projects," Energies, MDPI, vol. 10(12), pages 1-18, December.
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    4. Hongbo Shao & Yubin Mao & Yongmin Liu & Wanxun Liu & Sipei Sun & Peng Jia & Fufeng Miao & Li Yang & Chang Han & Bo Zhang, 2018. "A Three-Stage Procedure for Controlled Islanding to Prevent Wide-Area Blackouts," Energies, MDPI, vol. 11(11), pages 1-15, November.

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