IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i7p903-d103390.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/7/903/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/10/7/903/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Anh-Duc Nguyen & Van-Hai Bui & Akhtar Hussain & Duc-Huy Nguyen & Hak-Man Kim, 2018. "Impact of Demand Response Programs on Optimal Operation of Multi-Microgrid System," Energies, MDPI, vol. 11(6), pages 1-18, June.
    2. Akhtar Hussain & Van-Hai Bui & Hak-Man Kim, 2017. "Impact Analysis of Demand Response Intensity and Energy Storage Size on Operation of Networked Microgrids," Energies, MDPI, vol. 10(7), pages 1-19, June.
    3. Nah-Oak Song & Ji-Hye Lee & Hak-Man Kim, 2016. "Optimal Electric and Heat Energy Management of Multi-Microgrids with Sequentially-Coordinated Operations," Energies, MDPI, vol. 9(6), pages 1-18, June.
    4. Akhtar Hussain & Van-Hai Bui & Hak-Man Kim, 2016. "Robust Optimization-Based Scheduling of Multi-Microgrids Considering Uncertainties," Energies, MDPI, vol. 9(4), pages 1-21, April.
    5. Tine L. Vandoorn & Jan Van de Vyver & Louis Gevaert & Lieven Degroote & Lieven Vandevelde, 2015. "Congestion Control Algorithm in Distribution Feeders: Integration in a Distribution Management System," Energies, MDPI, vol. 8(6), pages 1-20, June.
    6. Miloud Rezkallah & Sanjeev Singh & Ambrish Chandra & Bhim Singh & Hussein Ibrahim, 2020. "Off-Grid System Configurations for Coordinated Control of Renewable Energy Sources," Energies, MDPI, vol. 13(18), pages 1-25, September.
    7. Jinyeong Lee & Kyungcheol Shin & Young-Min Wi, 2024. "Decentralized Operations of Industrial Complex Microgrids Considering Corporate Power Purchase Agreements for Renewable Energy 100% Initiatives in South Korea," Sustainability, MDPI, vol. 16(13), pages 1-24, June.
    8. Ming-Tse Kuo & Shiue-Der Lu, 2013. "Design and Implementation of Real-Time Intelligent Control and Structure Based on Multi-Agent Systems in Microgrids," Energies, MDPI, vol. 6(11), pages 1-15, November.
    9. Ahmad Khan, Aftab & Naeem, Muhammad & Iqbal, Muhammad & Qaisar, Saad & Anpalagan, Alagan, 2016. "A compendium of optimization objectives, constraints, tools and algorithms for energy management in microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1664-1683.
    10. 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).
    11. Hong-Chao Gao & Joon-Ho Choi & Sang-Yun Yun & Seon-Ju Ahn, 2020. "A New Power Sharing Scheme of Multiple Microgrids and an Iterative Pairing-Based Scheduling Method," Energies, MDPI, vol. 13(7), pages 1-20, April.
    12. Fan, Dongming & Ren, Yi & Feng, Qiang & Liu, Yiliu & Wang, Zili & Lin, Jing, 2021. "Restoration of smart grids: Current status, challenges, and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    13. Thai-Thanh Nguyen & Hyeong-Jun Yoo & Hak-Man Kim, 2015. "Application of Model Predictive Control to BESS for Microgrid Control," Energies, MDPI, vol. 8(8), pages 1-16, August.
    14. Im, Yong-Hoon & Liu, Jie, 2018. "Feasibility study on the low temperature district heating and cooling system with bi-lateral heat trades model," Energy, Elsevier, vol. 153(C), pages 988-999.
    15. Raya-Armenta, Jose Maurilio & Bazmohammadi, Najmeh & Avina-Cervantes, Juan Gabriel & Sáez, Doris & Vasquez, Juan C. & Guerrero, Josep M., 2021. "Energy management system optimization in islanded microgrids: An overview and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    16. Hua Han & Lang Li & Lina Wang & Mei Su & Yue Zhao & Josep M. Guerrero, 2017. "A Novel Decentralized Economic Operation in Islanded AC Microgrids," Energies, MDPI, vol. 10(6), pages 1-18, June.
    17. Shen, Xiaojun & Wei, Hongyang & Wei, Li, 2020. "Study of trackside photovoltaic power integration into the traction power system of suburban elevated urban rail transit line," Applied Energy, Elsevier, vol. 260(C).
    18. Iulia Stamatescu & Nicoleta Arghira & Ioana Făgărăşan & Grigore Stamatescu & Sergiu Stelian Iliescu & Vasile Calofir, 2017. "Decision Support System for a Low Voltage Renewable Energy System," Energies, MDPI, vol. 10(1), pages 1-15, January.
    19. V, Kavitha & V, Malathi & Guerrero, Josep M. & Bazmohammadi, Najmeh, 2022. "Energy management system using Mimosa Pudica optimization technique for microgrid applications," Energy, Elsevier, vol. 244(PA).
    20. Mayank Singh & Rakesh Chandra Jha, 2019. "Object-Oriented Usability Indices for Multi-Objective Demand Side Management Using Teaching-Learning Based Optimization," Energies, MDPI, vol. 12(3), pages 1-25, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:903-:d:103390. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.