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Robust Power Supply Restoration for Self-Healing Active Distribution Networks Considering the Availability of Distributed Generation

Author

Listed:
  • Qiang Yang

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

  • Le Jiang

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

  • Ali Ehsan

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

  • Yajing Gao

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Baoding 071003, China)

  • Shixiao Guo

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Baoding 071003, China)

Abstract

The increasing penetration of distributed generations (DGs) with intermittent and stochastic characteristics into current power distribution networks can lead to increased fault levels and degradation in network protection. As one of the key requirements of active network management (ANM), efficient power supply restoration solution to guarantee network self-healing capability with full consideration of DG uncertainties is demanded. This paper presents a joint power supply restoration through combining the DG local restoration and switcher operation-based restoration to enhance the self-healing capability in active distribution networks considering the availability of distributed generation. The restoration algorithmic solution is designed to be able to carry out power restoration in parallel upon multiple simultaneous faults to maximize the load restoration while additionally minimizing power loss, topology variation and power flow changes due to switcher operations. The performance of the proposed solution is validated based on a 53-bus distribution network with wind power generators through extensive simulation experiments for a range of fault cases and DG scenarios generated based on Heuristic Moment Matching (HMM) method to fully consider the DG randomness. The numerical result in comparison with the existing solutions demonstrates the effectiveness of the proposed power supply restoration solution.

Suggested Citation

  • Qiang Yang & Le Jiang & Ali Ehsan & Yajing Gao & Shixiao Guo, 2018. "Robust Power Supply Restoration for Self-Healing Active Distribution Networks Considering the Availability of Distributed Generation," Energies, MDPI, vol. 11(1), pages 1-19, January.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:1:p:210-:d:127023
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    References listed on IDEAS

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    1. Abdullah, M.A. & Agalgaonkar, A.P. & Muttaqi, K.M., 2014. "Assessment of energy supply and continuity of service in distribution network with renewable distributed generation," Applied Energy, Elsevier, vol. 113(C), pages 1015-1026.
    2. Coelho, Vitor N. & Weiss Cohen, Miri & Coelho, Igor M. & Liu, Nian & Guimarães, Frederico Gadelha, 2017. "Multi-agent systems applied for energy systems integration: State-of-the-art applications and trends in microgrids," Applied Energy, Elsevier, vol. 187(C), pages 820-832.
    3. Ding, Tao & Lin, Yanling & Bie, Zhaohong & Chen, Chen, 2017. "A resilient microgrid formation strategy for load restoration considering master-slave distributed generators and topology reconfiguration," Applied Energy, Elsevier, vol. 199(C), pages 205-216.
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    Cited by:

    1. Alexander Vinogradov & Vadim Bolshev & Alina Vinogradova & Michał Jasiński & Tomasz Sikorski & Zbigniew Leonowicz & Radomir Goňo & Elżbieta Jasińska, 2020. "Analysis of the Power Supply Restoration Time after Failures in Power Transmission Lines," Energies, MDPI, vol. 13(11), pages 1-18, May.

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