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Preventive Security-Constrained Optimal Power Flow Considering UPFC Control Modes

Author

Listed:
  • Xi Wu

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Zhengyu Zhou

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Gang Liu

    (Jiangsu Electric Power Company Economic Research Institute, Nanjing 211102, China)

  • Wanchun Qi

    (Jiangsu Electric Power Company Economic Research Institute, Nanjing 211102, China)

  • Zhenjian Xie

    (Jiangsu Electric Power Company Economic Research Institute, Nanjing 211102, China)

Abstract

The successful application of the unified power flow controller (UPFC) provides a new control method for the secure and economic operation of power system. In order to make the full use of UPFC and improve the economic efficiency and static security of a power system, a preventive security-constrained power flow optimization method considering UPFC control modes is proposed in this paper. Firstly, an iterative method considering UPFC control modes is deduced for power flow calculation. Taking into account the influence of different UPFC control modes on the distribution of power flow after N-1 contingency, the optimization model is then constructed by setting a minimal system operation cost and a maximum static security margin as the objective. Based on this model, the particle swarm optimization (PSO) algorithm is utilized to optimize power system operating parameters and UPFC control modes simultaneously. Finally, a standard IEEE 30-bus system is utilized to demonstrate that the proposed method fully exploits the potential of static control of UPFC and significantly increases the economic efficiency and static security of the power system.

Suggested Citation

  • Xi Wu & Zhengyu Zhou & Gang Liu & Wanchun Qi & Zhenjian Xie, 2017. "Preventive Security-Constrained Optimal Power Flow Considering UPFC Control Modes," Energies, MDPI, vol. 10(8), pages 1-15, August.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:8:p:1199-:d:108117
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    References listed on IDEAS

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    1. Kyungsung An & Kyung-Bin Song & Kyeon Hur, 2017. "Incorporating Charging/Discharging Strategy of Electric Vehicles into Security-Constrained Optimal Power Flow to Support High Renewable Penetration," Energies, MDPI, vol. 10(5), pages 1-15, May.
    2. Joaquim Monteiro & Sónia Pinto & Aranzazu Delgado Martin & José Fernando Silva, 2017. "A New Real Time Lyapunov Based Controller for Power Quality Improvement in Unified Power Flow Controllers Using Direct Matrix Converters," Energies, MDPI, vol. 10(6), pages 1-13, June.
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    Cited by:

    1. Sirote Khunkitti & Apirat Siritaratiwat & Suttichai Premrudeepreechacharn & Rongrit Chatthaworn & Neville R. Watson, 2018. "A Hybrid DA-PSO Optimization Algorithm for Multiobjective Optimal Power Flow Problems," Energies, MDPI, vol. 11(9), pages 1-21, August.
    2. Victor H. Hinojosa & Francisco Gonzalez-Longatt, 2018. "Preventive Security-Constrained DCOPF Formulation Using Power Transmission Distribution Factors and Line Outage Distribution Factors," Energies, MDPI, vol. 11(6), pages 1-13, June.
    3. Luis M. Leon & Arturo S. Bretas & Sergio Rivera, 2020. "Quadratically Constrained Quadratic Programming Formulation of Contingency Constrained Optimal Power Flow with Photovoltaic Generation," Energies, MDPI, vol. 13(13), pages 1-21, June.
    4. 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.
    5. Victor H. Hinojosa, 2020. "Comparing Corrective and Preventive Security-Constrained DCOPF Problems Using Linear Shift-Factors," Energies, MDPI, vol. 13(3), pages 1-16, January.

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