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A Decentralized Multi-Agent-Based Approach for Low Voltage Microgrid Restoration

Author

Listed:
  • Ebrahim Rokrok

    (Centre for Mechanical and Aerospace Science and Technologies (C-MAST), University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilhã, Portugal)

  • Miadreza Shafie-khah

    (Centre for Mechanical and Aerospace Science and Technologies (C-MAST), University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilhã, Portugal)

  • Pierluigi Siano

    (Department of Industrial Engineering, University of Salerno, 84084 Fisciano (SA), Italy)

  • João P. S. Catalão

    (Centre for Mechanical and Aerospace Science and Technologies (C-MAST), University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilhã, Portugal
    Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal
    Institute for Systems and Computer Engineering, Research and Development (INESC-ID), Instituto Superior Técnico, University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon, Portugal)

Abstract

Although a well-organized power system is less subject to blackouts, the existence of a proper restoration plan is nevertheless still essential. The goal of a restoration plan is to bring the power system back to its normal operating conditions in the shortest time after a blackout occurs and to minimize the impact of the blackout on society. This paper presents a decentralized multi-agent system (MAS)-based restoration method for a low voltage (LV) microgrid (MG). In the proposed method, the MG local controllers are assigned to the specific agents who interact with each other to achieve a common decision in the restoration procedure. The evaluation of the proposed decentralized technique using a benchmark low-voltage MG network demonstrates the effectiveness of the proposed restoration plan.

Suggested Citation

  • Ebrahim Rokrok & Miadreza Shafie-khah & Pierluigi Siano & João P. S. Catalão, 2017. "A Decentralized Multi-Agent-Based Approach for Low Voltage Microgrid Restoration," Energies, MDPI, vol. 10(10), pages 1-20, September.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:10:p:1491-:d:113409
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    References listed on IDEAS

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    1. Palizban, Omid & Kauhaniemi, Kimmo, 2015. "Hierarchical control structure in microgrids with distributed generation: Island and grid-connected mode," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 797-813.
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    Cited by:

    1. Pedro Faria, 2019. "Distributed Energy Resources Management," Energies, MDPI, vol. 12(3), pages 1-3, February.
    2. Pedro Faria & Zita Vale, 2019. "A Demand Response Approach to Scheduling Constrained Load Shifting," Energies, MDPI, vol. 12(9), pages 1-16, May.
    3. Junho Hong & Dmitry Ishchenko & Anil Kondabathini, 2021. "Implementation of Resilient Self-Healing Microgrids with IEC 61850-Based Communications," Energies, MDPI, vol. 14(3), pages 1-16, January.
    4. João Abel Peças Lopes & André Guimarães Madureira & Manuel Matos & Ricardo Jorge Bessa & Vítor Monteiro & João Luiz Afonso & Sérgio F. Santos & João P. S. Catalão & Carlos Henggeler Antunes & Pedro Ma, 2020. "The future of power systems: Challenges, trends, and upcoming paradigms," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 9(3), May.
    5. Amrutha Raju Battula & Sandeep Vuddanti & Surender Reddy Salkuti, 2021. "Review of Energy Management System Approaches in Microgrids," Energies, MDPI, vol. 14(17), pages 1-32, September.
    6. Mi Dong & Li Li & Lina Wang & Dongran Song & Zhangjie Liu & Xiaoyu Tian & Zhengguo Li & Yinghua Wang, 2018. "A Distributed Secondary Control Algorithm for Automatic Generation Control Considering EDP and Automatic Voltage Control in an AC Microgrid," Energies, MDPI, vol. 11(4), pages 1-18, April.
    7. Francisco Quinteros & Diego Carrión & Manuel Jaramillo, 2022. "Optimal Power Systems Restoration Based on Energy Quality and Stability Criteria," Energies, MDPI, vol. 15(6), pages 1-23, March.

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