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Multiagent-Based Distributed Load Shedding for Islanded Microgrids

Author

Listed:
  • Xi Wu

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

  • Ping Jiang

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

  • Jing Lu

    (NARI-Relays Electric CO., LTD, Nanjing 211100, China)

Abstract

This paper addresses a multiagent-based distributed load shedding scheme to restore frequency for the microgrids during islanded operation. The objective of the proposed scheme is to realize a distributed load shedding considering its associated cost and the capacity of the flexible loads. There are two advantages of the proposed scheme: (1) it is a distributed scheme using average-consensus theorem, which can discover the global information when only communications between immediate neighboring agents are used, moreover it can meet the requirements of plug-and-play operations more easily than a centralized scheme; (2) it is a new adaptive load shedding through the comprehensive weights which take into accounts the cost of load shedding and the capacity of flexible loads, these comprehensive weights are evaluated locally by making use of the adaptability and intelligence characteristics of agents. Simulation results in power systems computer aided design (PSCAD) illustrate the validity and adaptability of the proposed load shedding scheme.

Suggested Citation

  • Xi Wu & Ping Jiang & Jing Lu, 2014. "Multiagent-Based Distributed Load Shedding for Islanded Microgrids," Energies, MDPI, vol. 7(9), pages 1-13, September.
    • Handle: RePEc:gam:jeners:v:7:y:2014:i:9:p:6050-6062:d:40266
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    References listed on IDEAS

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    1. Yujin Lim & Hak-Man Kim & Tetsuo Kinoshita, 2014. "Distributed Load-Shedding System for Agent-Based Autonomous Microgrid Operations," Energies, MDPI, vol. 7(1), pages 1-17, January.
    2. Cheol-Hee Yoo & Il-Yop Chung & Hak-Ju Lee & Sung-Soo Hong, 2013. "Intelligent Control of Battery Energy Storage for Multi-Agent Based Microgrid Energy Management," Energies, MDPI, vol. 6(10), pages 1-24, September.
    3. Hak-Man Kim & Tetsuo Kinoshita & Myong-Chul Shin, 2010. "A Multiagent System for Autonomous Operation of Islanded Microgrids Based on a Power Market Environment," Energies, MDPI, vol. 3(12), pages 1-19, December.
    4. Hak-Man Kim & Yujin Lim & Tetsuo Kinoshita, 2012. "An Intelligent Multiagent System for Autonomous Microgrid Operation," Energies, MDPI, vol. 5(9), pages 1-16, September.
    5. Zhe Xiao & Tinghua Li & Ming Huang & Jihong Shi & Jingjing Yang & Jiang Yu & Wei Wu, 2010. "Hierarchical MAS Based Control Strategy for Microgrid," Energies, MDPI, vol. 3(9), pages 1-17, September.
    6. Changsun Ahn & Huei Peng, 2013. "Decentralized and Real-Time Power Dispatch Control for an Islanded Microgrid Supported by Distributed Power Sources," Energies, MDPI, vol. 6(12), pages 1-16, December.
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    Cited by:

    1. 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.
    2. Zizzo, G. & Beccali, M. & Bonomolo, M. & Di Pietra, B. & Ippolito, M.G. & La Cascia, D. & Leone, G. & Lo Brano, V. & Monteleone, F., 2017. "A feasibility study of some DSM enabling solutions in small islands: The case of Lampedusa," Energy, Elsevier, vol. 140(P1), pages 1030-1046.
    3. Skrjanc, T. & Mihalic, R. & Rudez, U., 2023. "A systematic literature review on under-frequency load shedding protection using clustering methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 180(C).
    4. Woltmann, Stefan & Kittel, Julia, 2022. "Development and implementation of multi-agent systems for demand response aggregators in an industrial context," Applied Energy, Elsevier, vol. 314(C).

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