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A Survey on Smart Agent-Based Microgrids for Resilient/Self-Healing Grids

Author

Listed:
  • Kaveh Dehghanpour

    (Electrical and Computer Engineering, Montana State University, Bozeman, MT 59717, USA)

  • Christopher Colson

    (Western Area Power Administration, Billings, MT 59101, USA)

  • Hashem Nehrir

    (Electrical and Computer Engineering, Montana State University, Bozeman, MT 59717, USA)

Abstract

This paper presents an overview of our body of work on the application of smart control techniques for the control and management of microgrids (MGs). The main focus here is on the application of distributed multi-agent system (MAS) theory in multi-objective (MO) power management of MGs to find the Pareto-front of the MO power management problem. In addition, the paper presents the application of Nash bargaining solution (NBS) and the MAS theory to directly obtain the NBS on the Pareto-front. The paper also discusses the progress reported on the above issues from the literature. We also present a MG-based power system architecture for enhancing the resilience and self-healing of the system.

Suggested Citation

  • Kaveh Dehghanpour & Christopher Colson & Hashem Nehrir, 2017. "A Survey on Smart Agent-Based Microgrids for Resilient/Self-Healing Grids," Energies, MDPI, vol. 10(5), pages 1-25, May.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:5:p:620-:d:97432
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    References listed on IDEAS

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    6. Pol Olivella-Rosell & Roberto Villafafila-Robles & Andreas Sumper & Joan Bergas-Jané, 2015. "Probabilistic Agent-Based Model of Electric Vehicle Charging Demand to Analyse the Impact on Distribution Networks," Energies, MDPI, vol. 8(5), pages 1-28, May.
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    Cited by:

    1. Hussain, Akhtar & Bui, Van-Hai & Kim, Hak-Man, 2019. "Microgrids as a resilience resource and strategies used by microgrids for enhancing resilience," Applied Energy, Elsevier, vol. 240(C), pages 56-72.
    2. Abedi, Amin & Gaudard, Ludovic & Romerio, Franco, 2019. "Review of major approaches to analyze vulnerability in power system," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 153-172.
    3. Fauzan Hanif Jufri & Jun-Sung Kim & Jaesung Jung, 2017. "Analysis of Determinants of the Impact and the Grid Capability to Evaluate and Improve Grid Resilience from Extreme Weather Event," Energies, MDPI, vol. 10(11), pages 1-17, November.
    4. Hossein Shayeghi & Elnaz Shahryari & Mohammad Moradzadeh & Pierluigi Siano, 2019. "A Survey on Microgrid Energy Management Considering Flexible Energy Sources," Energies, MDPI, vol. 12(11), pages 1-26, June.
    5. Shobole, Abdulfetah Abdela & Wadi, Mohammed, 2021. "Multiagent systems application for the smart grid protection," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    6. Zagros Shahooei & Lane Martin & Hashem Nehrir & Maryam Bahramipanah, 2022. "A Novel Agent-Based Power Management Scheme for Smart Multiple-Microgrid Distribution Systems," Energies, MDPI, vol. 15(5), pages 1-13, February.
    7. Lucrezia Manservigi & Mattia Cattozzo & Pier Ruggero Spina & Mauro Venturini & Hilal Bahlawan, 2020. "Optimal Management of the Energy Flows of Interconnected Residential Users," Energies, MDPI, vol. 13(6), pages 1-21, March.
    8. Silvia Marzal & Raul González-Medina & Robert Salas-Puente & Emilio Figueres & Gabriel Garcerá, 2017. "A Novel Locality Algorithm and Peer-to-Peer Communication Infrastructure for Optimizing Network Performance in Smart Microgrids," Energies, MDPI, vol. 10(9), pages 1-25, August.
    9. Patnaik, Bhaskar & Mishra, Manohar & Bansal, Ramesh C. & Jena, Ranjan Kumar, 2020. "AC microgrid protection – A review: Current and future prospective," Applied Energy, Elsevier, vol. 271(C).

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