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Hierarchical MAS Based Control Strategy for Microgrid

Author

Listed:
  • Zhe Xiao

    (School of Information Science and Engineering, Yunnan University, Kunming 650091, China
    School of Electrical & Electronic Engineering, Nanyang Technological University ,Western Catchment Area, 639798, Singapore)

  • Tinghua Li

    (School of Information Science and Engineering, Yunnan University, Kunming 650091, China)

  • Ming Huang

    (School of Information Science and Engineering, Yunnan University, Kunming 650091, China)

  • Jihong Shi

    (School of Information Science and Engineering, Yunnan University, Kunming 650091, China)

  • Jingjing Yang

    (School of Information Science and Engineering, Yunnan University, Kunming 650091, China)

  • Jiang Yu

    (School of Information Science and Engineering, Yunnan University, Kunming 650091, China)

  • Wei Wu

    (Communication Branch of Yunnan Power Grid Corporation, Kunming, Yunnan 650217, China)

Abstract

Microgrids have become a hot topic driven by the dual pressures of environmental protection concerns and the energy crisis. In this paper, a challenge for the distributed control of a modern electric grid incorporating clusters of residential microgrids is elaborated and a hierarchical multi-agent system (MAS) is proposed as a solution. The issues of how to realize the hierarchical MAS and how to improve coordination and control strategies are discussed. Based on MATLAB and ZEUS platforms, bilateral switching between grid-connected mode and island mode is performed under control of the proposed MAS to enhance and support its effectiveness.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:3:y:2010:i:9:p:1622-1638:d:9549
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    References listed on IDEAS

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    Cited by:

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    2. Khan, Muhammad Waseem & Wang, Jie, 2017. "The research on multi-agent system for microgrid control and optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1399-1411.
    3. Zhirong Xu & Ping Yang & Zhiji Zeng & Jiajun Peng & Zhuoli Zhao, 2016. "Black Start Strategy for PV-ESS Multi-Microgrids with Three-Phase/Single-Phase Architecture," Energies, MDPI, vol. 9(5), pages 1-14, May.
    4. Vasiliki Vita & Georgios Fotis & Christos Pavlatos & Valeri Mladenov, 2023. "A New Restoration Strategy in Microgrids after a Blackout with Priority in Critical Loads," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
    5. Khaizaran Abdulhussein Al Sumarmad & Nasri Sulaiman & Noor Izzri Abdul Wahab & Hashim Hizam, 2022. "Microgrid Energy Management System Based on Fuzzy Logic and Monitoring Platform for Data Analysis," Energies, MDPI, vol. 15(11), pages 1-19, June.
    6. 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.
    7. Xi Wu & Ping Jiang & Jing Lu, 2014. "Multiagent-Based Distributed Load Shedding for Islanded Microgrids," Energies, MDPI, vol. 7(9), pages 1-13, September.
    8. Fatma Yaprakdal & M. Berkay Yılmaz & Mustafa Baysal & Amjad Anvari-Moghaddam, 2020. "A Deep Neural Network-Assisted Approach to Enhance Short-Term Optimal Operational Scheduling of a Microgrid," Sustainability, MDPI, vol. 12(4), pages 1-27, February.
    9. 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.
    10. Abdul Conteh & Mohammed Elsayed Lotfy & Oludamilare Bode Adewuyi & Paras Mandal & Hiroshi Takahashi & Tomonobu Senjyu, 2020. "Demand Response Economic Assessment with the Integration of Renewable Energy for Developing Electricity Markets," Sustainability, MDPI, vol. 12(7), pages 1-20, March.
    11. Jorge J. Gomez-Sanz & Sandra Garcia-Rodriguez & Nuria Cuartero-Soler & Luis Hernandez-Callejo, 2014. "Reviewing Microgrids from a Multi-Agent Systems Perspective," Energies, MDPI, vol. 7(5), pages 1-28, May.
    12. Henan Dong & Shun Yuan & Zijiao Han & Zhiyuan Cai & Guangdong Jia & Yangyang Ge, 2018. "A Comprehensive Strategy for Accurate Reactive Power Distribution, Stability Improvement, and Harmonic Suppression of Multi-Inverter-Based Micro-Grid," Energies, MDPI, vol. 11(4), pages 1-16, March.
    13. 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.
    14. 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.
    15. Manbachi, Moein & Farhangi, Hassan & Palizban, Ali & Arzanpour, Siamak, 2016. "Smart grid adaptive energy conservation and optimization engine utilizing Particle Swarm Optimization and Fuzzification," Applied Energy, Elsevier, vol. 174(C), pages 69-79.
    16. Ying-Yi Hong & Jing-Han Chou, 2012. "Nonintrusive Energy Monitoring for Microgrids Using Hybrid Self-Organizing Feature-Mapping Networks," Energies, MDPI, vol. 5(7), pages 1-16, July.
    17. 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.
    18. Jing Wang & Longhua Mu & Fan Zhang & Xin Zhang, 2017. "A Parallel Restoration for Black Start of Microgrids Considering Characteristics of Distributed Generations," Energies, MDPI, vol. 11(1), pages 1-18, December.

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