IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v171y2019icp284-295.html
   My bibliography  Save this article

MAS-based distributed control method for multi-microgrids with high-penetration renewable energy

Author

Listed:
  • Li, Qiang
  • Gao, Mengkai
  • Lin, Houfei
  • Chen, Ziyu
  • Chen, Minyou

Abstract

The distributed control of a multi-microgrid (MMG) system composed of neighboring microgrids (MGs) is much more complex than that of an MG. In this paper, a fully distributed control method with fault tolerance control for MMG systems is proposed, which is a two-layer model, where a communication network composed of agents is the top layer, while an MMG is the bottom layer. Further, a systematic method is presented to obtain a set of distributed control laws for agents from any given communication network. The communication network consists of two types of subgraphs, a within-MG subgraph and a between-MG subgraph. Moreover, the control laws derived from the within-MG subgraph ensure the supply-demand balance and the proportional outputs of distributed generators (DGs) in each MG, while the control laws derived from the between-MG subgraph coordinate MGs to achieve the power balance of the MMG system. Furthermore, two theorems and a proposition are proved, which state the convergence of the derived control laws. Finally, simulations are carried out on the MMG model in MATLAB/Simulink. The results show that the frequencies and voltages in MGs stay at the prescribed values, and the proportional outputs are achieved, when both loads and environmental conditions fluctuate. Furthermore, our distributed method has higher tolerance to the failures of agents, when compared to a centralized method.

Suggested Citation

  • Li, Qiang & Gao, Mengkai & Lin, Houfei & Chen, Ziyu & Chen, Minyou, 2019. "MAS-based distributed control method for multi-microgrids with high-penetration renewable energy," Energy, Elsevier, vol. 171(C), pages 284-295.
  • Handle: RePEc:eee:energy:v:171:y:2019:i:c:p:284-295
    DOI: 10.1016/j.energy.2018.12.167
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544218325416
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2018.12.167?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mancarella, Pierluigi, 2014. "MES (multi-energy systems): An overview of concepts and evaluation models," Energy, Elsevier, vol. 65(C), pages 1-17.
    2. Jalali, Mehdi & Zare, Kazem & Seyedi, Heresh, 2017. "Strategic decision-making of distribution network operator with multi-microgrids considering demand response program," Energy, Elsevier, vol. 141(C), pages 1059-1071.
    3. Fang, Xinli & Yang, Qiang & Wang, Jianhui & Yan, Wenjun, 2016. "Coordinated dispatch in multiple cooperative autonomous islanded microgrids," Applied Energy, Elsevier, vol. 162(C), pages 40-48.
    4. Wu, Pan & Huang, Wentao & Tai, Nengling & Liang, Shuo, 2018. "A novel design of architecture and control for multiple microgrids with hybrid AC/DC connection," Applied Energy, Elsevier, vol. 210(C), pages 1002-1016.
    5. Wang, Dongxiao & Qiu, Jing & Reedman, Luke & Meng, Ke & Lai, Loi Lei, 2018. "Two-stage energy management for networked microgrids with high renewable penetration," Applied Energy, Elsevier, vol. 226(C), pages 39-48.
    6. Xie, Min & Ji, Xiang & Hu, Xintong & Cheng, Peijun & Du, Yuxin & Liu, Mingbo, 2018. "Autonomous optimized economic dispatch of active distribution system with multi-microgrids," Energy, Elsevier, vol. 153(C), pages 479-489.
    7. Fang, Xinli & Ma, Shihao & Yang, Qiang & Zhang, Jintao, 2016. "Cooperative energy dispatch for multiple autonomous microgrids with distributed renewable sources and storages," Energy, Elsevier, vol. 99(C), pages 48-57.
    8. Kou, Peng & Liang, Deliang & Gao, Lin, 2017. "Distributed EMPC of multiple microgrids for coordinated stochastic energy management," Applied Energy, Elsevier, vol. 185(P1), pages 939-952.
    9. Ju, Liwei & Zhang, Qi & Tan, Zhongfu & Wang, Wei & Xin, He & Zhang, Zehao, 2018. "Multi-agent-system-based coupling control optimization model for micro-grid group intelligent scheduling considering autonomy-cooperative operation strategy," Energy, Elsevier, vol. 157(C), pages 1035-1052.
    10. Wouters, Carmen & Fraga, Eric S. & James, Adrian M., 2015. "An energy integrated, multi-microgrid, MILP (mixed-integer linear programming) approach for residential distributed energy system planning – A South Australian case-study," Energy, Elsevier, vol. 85(C), pages 30-44.
    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. Tabar, Vahid Sohrabi & Abbasi, Vahid, 2019. "Energy management in microgrid with considering high penetration of renewable resources and surplus power generation problem," Energy, Elsevier, vol. 189(C).
    2. Hu, Mian & Wang, Yan-Wu & Xiao, Jiang-Wen & Lin, Xiangning, 2019. "Multi-energy management with hierarchical distributed multi-scale strategy for pelagic islanded microgrid clusters," Energy, Elsevier, vol. 185(C), pages 910-921.
    3. Karimi, Hamid & Jadid, Shahram, 2020. "Optimal energy management for multi-microgrid considering demand response programs: A stochastic multi-objective framework," Energy, Elsevier, vol. 195(C).
    4. Ahmadi, Seyed Ehsan & Sadeghi, Delnia & Marzband, Mousa & Abusorrah, Abdullah & Sedraoui, Khaled, 2022. "Decentralized bi-level stochastic optimization approach for multi-agent multi-energy networked micro-grids with multi-energy storage technologies," Energy, Elsevier, vol. 245(C).
    5. Nizami, M.S.H. & Haque, A.N.M.M. & Nguyen, P.H. & Hossain, M.J., 2019. "On the application of Home Energy Management Systems for power grid support," Energy, Elsevier, vol. 188(C).
    6. Qian, Tong & Tang, Wenhu & Wu, Qinghua, 2020. "A fully decentralized dual consensus method for carbon trading power dispatch with wind power," Energy, Elsevier, vol. 203(C).
    7. Naderi, Mobin & Khayat, Yousef & Shafiee, Qobad & Blaabjerg, Frede & Bevrani, Hassan, 2023. "Dynamic modeling, stability analysis and control of interconnected microgrids: A review," Applied Energy, Elsevier, vol. 334(C).
    8. Pavel Ilyushin & Vladislav Volnyi & Konstantin Suslov & Sergey Filippov, 2023. "State-of-the-Art Literature Review of Power Flow Control Methods for Low-Voltage AC and AC-DC Microgrids," Energies, MDPI, vol. 16(7), pages 1-35, March.
    9. Wu, Kunming & Li, Qiang & Chen, Ziyu & Lin, Jiayang & Yi, Yongli & Chen, Minyou, 2021. "Distributed optimization method with weighted gradients for economic dispatch problem of multi-microgrid systems," Energy, Elsevier, vol. 222(C).
    10. Kang, Wenfa & Chen, Minyou & Lai, Wei & Luo, Yanyu, 2021. "Distributed real-time power management for virtual energy storage systems using dynamic price," Energy, Elsevier, vol. 216(C).
    11. Diptish Saha & Najmeh Bazmohammadi & Juan C. Vasquez & Josep M. Guerrero, 2023. "Multiple Microgrids: A Review of Architectures and Operation and Control Strategies," Energies, MDPI, vol. 16(2), pages 1-32, January.
    12. Yuxin Wen & Peixiao Fan & Jia Hu & Song Ke & Fuzhang Wu & Xu Zhu, 2022. "An Optimal Scheduling Strategy of a Microgrid with V2G Based on Deep Q-Learning," Sustainability, MDPI, vol. 14(16), pages 1-18, August.
    13. Vladislav Volnyi & Pavel Ilyushin & Konstantin Suslov & Sergey Filippov, 2023. "Approaches to Building AC and AC–DC Microgrids on Top of Existing Passive Distribution Networks," Energies, MDPI, vol. 16(15), pages 1-26, August.
    14. Ronaldo Silveira Junior, Jose & Conrado, Bruna R.P. & Matheus dos Santos Alonso, Augusto & Iglesias Brandao, Danilo, 2023. "Interoperability of single-controllable clusters: Aggregate response of low-voltage microgrids," Applied Energy, Elsevier, vol. 340(C).
    15. Kong, Xiangyu & Liu, Dehong & Xiao, Jie & Wang, Chengshan, 2019. "A multi-agent optimal bidding strategy in microgrids based on artificial immune system," Energy, Elsevier, vol. 189(C).
    16. Romain Mannini & Julien Eynard & Stéphane Grieu, 2022. "A Survey of Recent Advances in the Smart Management of Microgrids and Networked Microgrids," Energies, MDPI, vol. 15(19), pages 1-37, September.
    17. Han, Dongho & Lee, Jay H., 2021. "Two-stage stochastic programming formulation for optimal design and operation of multi-microgrid system using data-based modeling of renewable energy sources," Applied Energy, Elsevier, vol. 291(C).
    18. Lilia Tightiz & Joon Yoo, 2022. "A Review on a Data-Driven Microgrid Management System Integrating an Active Distribution Network: Challenges, Issues, and New Trends," Energies, MDPI, vol. 15(22), pages 1-24, November.

    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. Nawaz, Arshad & Zhou, Min & Wu, Jing & Long, Chengnian, 2022. "A comprehensive review on energy management, demand response, and coordination schemes utilization in multi-microgrids network," Applied Energy, Elsevier, vol. 323(C).
    2. Diptish Saha & Najmeh Bazmohammadi & Juan C. Vasquez & Josep M. Guerrero, 2023. "Multiple Microgrids: A Review of Architectures and Operation and Control Strategies," Energies, MDPI, vol. 16(2), pages 1-32, January.
    3. Karimi, Hamid & Jadid, Shahram, 2020. "Optimal energy management for multi-microgrid considering demand response programs: A stochastic multi-objective framework," Energy, Elsevier, vol. 195(C).
    4. José Luis Ruiz Duarte & Neng Fan, 2022. "Operation of a Power Grid with Embedded Networked Microgrids and Onsite Renewable Technologies," Energies, MDPI, vol. 15(7), pages 1-24, March.
    5. Villanueva-Rosario, Junior Alexis & Santos-García, Félix & Aybar-Mejía, Miguel Euclides & Mendoza-Araya, Patricio & Molina-García, Angel, 2022. "Coordinated ancillary services, market participation and communication of multi-microgrids: A review," Applied Energy, Elsevier, vol. 308(C).
    6. Zhang, Bingying & Li, Qiqiang & Wang, Luhao & Feng, Wei, 2018. "Robust optimization for energy transactions in multi-microgrids under uncertainty," Applied Energy, Elsevier, vol. 217(C), pages 346-360.
    7. Ren, Lingyu & Qin, Yanyuan & Li, Yan & Zhang, Peng & Wang, Bing & Luh, Peter B. & Han, Song & Orekan, Taofeek & Gong, Tao, 2018. "Enabling resilient distributed power sharing in networked microgrids through software defined networking," Applied Energy, Elsevier, vol. 210(C), pages 1251-1265.
    8. David Grosspietsch & Marissa Saenger & Bastien Girod, 2019. "Matching decentralized energy production and local consumption: A review of renewable energy systems with conversion and storage technologies," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(4), July.
    9. Woong Ko & Jong-Keun Park & Mun-Kyeom Kim & Jae-Haeng Heo, 2017. "A Multi-Energy System Expansion Planning Method Using a Linearized Load-Energy Curve: A Case Study in South Korea," Energies, MDPI, vol. 10(10), pages 1-24, October.
    10. Kong, Xiangyu & Liu, Dehong & Wang, Chengshan & Sun, Fangyuan & Li, Shupeng, 2020. "Optimal operation strategy for interconnected microgrids in market environment considering uncertainty," Applied Energy, Elsevier, vol. 275(C).
    11. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.
    12. Zhang, Xiaoshun & Yu, Tao & Xu, Zhao & Fan, Zhun, 2018. "A cyber-physical-social system with parallel learning for distributed energy management of a microgrid," Energy, Elsevier, vol. 165(PA), pages 205-221.
    13. Álex Omar Topa Gavilema & José Domingo Álvarez & José Luis Torres Moreno & Manuel Pérez García, 2021. "Towards Optimal Management in Microgrids: An Overview," Energies, MDPI, vol. 14(16), pages 1-25, August.
    14. Heendeniya, Charitha Buddhika & Sumper, Andreas & Eicker, Ursula, 2020. "The multi-energy system co-planning of nearly zero-energy districts – Status-quo and future research potential," Applied Energy, Elsevier, vol. 267(C).
    15. Sui, Quan & Zhang, Rui & Wu, Chuantao & Wei, Fanrong & Lin, Xiangning & Li, Zhengtian, 2020. "Stochastic scheduling of an electric vessel-based energy management system in pelagic clustering islands," Applied Energy, Elsevier, vol. 259(C).
    16. Tang, Chong & Liu, Mingbo & Dai, Yue & Wang, Zhijun & Xie, Min, 2019. "Decentralized saddle-point dynamics solution for optimal power flow of distribution systems with multi-microgrids," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    17. Bandeiras, F. & Pinheiro, E. & Gomes, M. & Coelho, P. & Fernandes, J., 2020. "Review of the cooperation and operation of microgrid clusters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    18. Klemm, Christian & Vennemann, Peter, 2021. "Modeling and optimization of multi-energy systems in mixed-use districts: A review of existing methods and approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    19. Han, Dongho & Lee, Jay H., 2021. "Two-stage stochastic programming formulation for optimal design and operation of multi-microgrid system using data-based modeling of renewable energy sources," Applied Energy, Elsevier, vol. 291(C).
    20. Zhu, Ziqing & Wing Chan, Ka & Bu, Siqi & Zhou, Bin & Xia, Shiwei, 2021. "Real-Time interaction of active distribution network and virtual microgrids: Market paradigm and data-driven stakeholder behavior analysis," Applied Energy, Elsevier, vol. 297(C).

    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:eee:energy:v:171:y:2019:i:c:p:284-295. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.