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Diffusion Strategy-Based Distributed Operation of Microgrids Using Multiagent System

Author

Listed:
  • Van-Hai Bui

    (Department of Electrical Engineering, Incheon National University, 12-1 Songdo-dong, Yeonsu-gu, Incheon 406840, Korea)

  • Akhtar Hussain

    (Department of Electrical Engineering, Incheon National University, 12-1 Songdo-dong, Yeonsu-gu, Incheon 406840, Korea)

  • Hak-Man Kim

    (Department of Electrical Engineering, Incheon National University, 12-1 Songdo-dong, Yeonsu-gu, Incheon 406840, Korea
    Research Institute for Northeast Asian Super Grid, Incheon National University, 12-1 Songdo-dong, Yeonsu-gu, Incheon 406840, Korea)

Abstract

In distributed operation, each unit is operated by its local controller instead of using a centralized controller, which allows the action to be based on local information rather than global information. Most of the distributed solutions have implemented the consensus method, however, convergence time of the consensus method is quite long, while diffusion strategy includes a stochastic gradient term and can reach convergence much faster compared with consensus method. Therefore, in this paper, a diffusion strategy-based distributed operation of microgrids (MGs) is proposed using multiagent system for both normal and emergency operation modes. In normal operation, the MG system is operated by a central controller instead of the distributed controller to minimize the operation cost. If any event (fault) occurs in the system, MG system can be divided into two parts to isolate the faulty region. In this case, the MG system is changed to emergency operation mode. The normal part is rescheduled by the central controller while the isolated part schedules its resources in a distributed manner. The isolated part carries out distributed communication using diffusion between neighboring agents for optimal operation of this part. The proposed method enables peer-to-peer communication among the agents without the necessity of a centralized controller, and simultaneously performs resource optimization. Simulation results show that the system can be operated in an economic way in both normal operation and emergency operation modes.

Suggested Citation

  • Van-Hai Bui & Akhtar Hussain & Hak-Man Kim, 2017. "Diffusion Strategy-Based Distributed Operation of Microgrids Using Multiagent System," Energies, MDPI, vol. 10(7), pages 1-21, July.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:903-:d:103390
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    References listed on IDEAS

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    1. Yao Liu & Xiaochao Hou & Xiaofeng Wang & Chao Lin & Josep M. Guerrero, 2016. "A Coordinated Control for Photovoltaic Generators and Energy Storages in Low-Voltage AC/DC Hybrid Microgrids under Islanded Mode," Energies, MDPI, vol. 9(8), pages 1-15, August.
    2. 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.
    3. Hee-Jun Cha & Dong-Jun Won & Sang-Hyuk Kim & Il-Yop Chung & Byung-Moon Han, 2015. "Multi-Agent System-Based Microgrid Operation Strategy for Demand Response," Energies, MDPI, vol. 8(12), pages 1-15, December.
    4. Nah-Oak Song & Ji-Hye Lee & Hak-Man Kim & Yong Hoon Im & Jae Yong Lee, 2015. "Optimal Energy Management of Multi-Microgrids with Sequentially Coordinated Operations," Energies, MDPI, vol. 8(8), pages 1-20, August.
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    Cited by:

    1. Van-Hai Bui & Akhtar Hussain & Woon-Gyu Lee & Hak-Man Kim, 2019. "Hybrid Energy Management System for Operation of Wind Farm System Considering Grid-Code Constraints," Energies, MDPI, vol. 12(24), pages 1-19, December.
    2. Pedro Faria, 2019. "Distributed Energy Resources Management," Energies, MDPI, vol. 12(3), pages 1-3, February.
    3. Bui, Van-Hai & Hussain, Akhtar & Im, Yong-Hoon & Kim, Hak-Man, 2019. "An internal trading strategy for optimal energy management of combined cooling, heat and power in building microgrids," Applied Energy, Elsevier, vol. 239(C), pages 536-548.
    4. Zhilin Lyu & Xiao Yang & Yiyi Zhang & Junhui Zhao, 2020. "Bi-Level Optimal Strategy of Islanded Multi-Microgrid Systems Based on Optimal Power Flow and Consensus Algorithm," Energies, MDPI, vol. 13(7), pages 1-19, March.
    5. Su-Been Hong & Thai-Thanh Nguyen & Jinhong Jeon & Hak-Man Kim, 2020. "Distributed Operation of Microgrids Considering Secondary Frequency Restoration Based on the Diffusion Algorithm," Energies, MDPI, vol. 13(12), pages 1-14, June.
    6. Haesum Ali & Akhtar Hussain & Van-Hai Bui & Jinhong Jeon & Hak-Man Kim, 2019. "Welfare Maximization-Based Distributed Demand Response for Islanded Multi-Microgrid Networks Using Diffusion Strategy," Energies, MDPI, vol. 12(19), pages 1-18, September.
    7. K/bidi, Fabrice & Damour, Cedric & Grondin, Dominique & Hilairet, Mickaël & Benne, Michel, 2022. "Multistage power and energy management strategy for hybrid microgrid with photovoltaic production and hydrogen storage," Applied Energy, Elsevier, vol. 323(C).

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