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A Multi-Objective Optimization Approach for Corrective Switching of Transmission Systems in Emergency Scenarios

Author

Listed:
  • Xin Xu

    (Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education, Shandong University, Jinan 250061, China)

  • Yongji Cao

    (Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education, Shandong University, Jinan 250061, China)

  • Hengxu Zhang

    (Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education, Shandong University, Jinan 250061, China)

  • Shiying Ma

    (China Electric Power Research Institute, Beijing 100192, China)

  • Yunting Song

    (China Electric Power Research Institute, Beijing 100192, China)

  • Dezhi Chen

    (China Electric Power Research Institute, Beijing 100192, China)

Abstract

The large capacity transmission of power over long distance and the rapid development of renewable energy increase the probability of unexpected emergencies such as overload and under-voltage. To tackle these emergencies and defend future disturbances, the corrective switching is implemented as an online control and a multi-objective scheme-making approach is proposed. A multi-objective 0-1 integer optimization model is established to cover a set of contradictory objectives from the aspects of economics, security and reliability. A two-phase optimization approach is proposed to ensure computation efficiency and coordinate the trade-off between these objectives: in the first phase, a feasible set silting method is utilized to quickly search for a set of candidate corrective switching schemes; in the second phase, the technique for order preference by similarity to an ideal solution (TOPSIS) method is applied to the candidate set to coordinate the contradictory objectives and determine the ultimate engineering scheme. Two case studies are conducted to verify the proposed approach in overload and under-voltage scenarios. The results are discussed to show the strengths when the performance indices of economics, security and reliability are considered.

Suggested Citation

  • Xin Xu & Yongji Cao & Hengxu Zhang & Shiying Ma & Yunting Song & Dezhi Chen, 2017. "A Multi-Objective Optimization Approach for Corrective Switching of Transmission Systems in Emergency Scenarios," Energies, MDPI, vol. 10(8), pages 1-19, August.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:8:p:1204-:d:108255
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    References listed on IDEAS

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    1. Ho-Young Kim & Mun-Kyeom Kim & San Kim, 2017. "Multi-Objective Scheduling Optimization Based on a Modified Non-Dominated Sorting Genetic Algorithm-II in Voltage Source Converter−Multi-Terminal High Voltage DC Grid-Connected Offshore Wind Farms wit," Energies, MDPI, vol. 10(7), pages 1-21, July.
    2. Mahesh Kumar & Perumal Nallagownden & Irraivan Elamvazuthi, 2017. "Optimal Placement and Sizing of Renewable Distributed Generations and Capacitor Banks into Radial Distribution Systems," Energies, MDPI, vol. 10(6), pages 1-25, June.
    3. 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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    Cited by:

    1. Juan Toctaquiza & Diego Carrión & Manuel Jaramillo, 2023. "An Electrical Power System Reconfiguration Model Based on Optimal Transmission Switching under Scenarios of Intentional Attacks," Energies, MDPI, vol. 16(6), pages 1-17, March.

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