IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v174y2019icp576-590.html
   My bibliography  Save this article

Real-time operation of multi-micro-grids using a multi-agent system

Author

Listed:
  • Keshta, H.E.
  • Ali, A.A.
  • Saied, E.M.
  • Bendary, F.M.

Abstract

The inaccurate prediction of solar irradiance, wind speed and demand load may significantly influence the operation of micro-grids. This condition causes unbalances between generation and load that lead to variations in DC and AC bus voltages, and may affect system stability. A multi-agent system (MAS) is proposed in this study to achieve optimal energy management for voltage regulation and to enhance the stability of a system under different weather conditions and load perturbations for two connected micro-grids. Optimum operation is achieved through two stages. The first stage is the optimum day-ahead energy from each source based on historical data. The second stage is implemented to maintain the balance between generation and load by considering economic operation during real-time operation. This stage can be realized by controlling converters related to each source in both micro-grids. Different scenarios are presented to evaluate the effectiveness of the proposed MAS. The simulation results demonstrate that the performance of the proposed energy management system is efficient.

Suggested Citation

  • Keshta, H.E. & Ali, A.A. & Saied, E.M. & Bendary, F.M., 2019. "Real-time operation of multi-micro-grids using a multi-agent system," Energy, Elsevier, vol. 174(C), pages 576-590.
    • Handle: RePEc:eee:energy:v:174:y:2019:i:c:p:576-590
    DOI: 10.1016/j.energy.2019.02.145
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544219303445
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2019.02.145?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. Wei-Tzer Huang & Kai-Chao Yao & Chun-Ching Wu, 2014. "Using the Direct Search Method for Optimal Dispatch of Distributed Generation in a Medium-Voltage Microgrid," Energies, MDPI, vol. 7(12), pages 1-19, December.
    2. Nemati, Mohsen & Braun, Martin & Tenbohlen, Stefan, 2018. "Optimization of unit commitment and economic dispatch in microgrids based on genetic algorithm and mixed integer linear programming," Applied Energy, Elsevier, vol. 210(C), pages 944-963.
    3. Marzband, Mousa & Ghadimi, Majid & Sumper, Andreas & Domínguez-García, José Luis, 2014. "Experimental validation of a real-time energy management system using multi-period gravitational search algorithm for microgrids in islanded mode," Applied Energy, Elsevier, vol. 128(C), pages 164-174.
    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. Jiao, P.H. & Chen, J.J. & Peng, K. & Zhao, Y.L. & Xin, K.F., 2020. "Multi-objective mean-semi-entropy model for optimal standalone micro-grid planning with uncertain renewable energy resources," Energy, Elsevier, vol. 191(C).
    2. Md Mainul Islam & Mahmood Nagrial & Jamal Rizk & Ali Hellany, 2021. "General Aspects, Islanding Detection, and Energy Management in Microgrids: A Review," Sustainability, MDPI, vol. 13(16), pages 1-45, August.
    3. Cui, Shiting & Gao, Yao & Zhu, Ruijin, 2024. "A new integrated energy system cluster energy sharing framework adapted to high altitude areas," Applied Energy, Elsevier, vol. 366(C).
    4. Pan, Chenyun & Fan, Hongtao & Zhang, Ruixiang & Sun, Jie & Wang, Yu & Sun, Yaojie, 2023. "An improved multi-timescale coordinated control strategy for an integrated energy system with a hybrid energy storage system," Applied Energy, Elsevier, vol. 343(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. Zhang, Xizheng & Wang, Zeyu & Lu, Zhangyu, 2022. "Multi-objective load dispatch for microgrid with electric vehicles using modified gravitational search and particle swarm optimization algorithm," Applied Energy, Elsevier, vol. 306(PA).
    2. Yamashita, Daniela Yassuda & Vechiu, Ionel & Gaubert, Jean-Paul, 2020. "A review of hierarchical control for building microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
    3. Cagnano, A. & Caldarulo Bugliari, A. & De Tuglie, E., 2018. "A cooperative control for the reserve management of isolated microgrids," Applied Energy, Elsevier, vol. 218(C), pages 256-265.
    4. Abdellatif Elmouatamid & Radouane Ouladsine & Mohamed Bakhouya & Najib El Kamoun & Mohammed Khaidar & Khalid Zine-Dine, 2020. "Review of Control and Energy Management Approaches in Micro-Grid Systems," Energies, MDPI, vol. 14(1), pages 1-30, December.
    5. 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).
    6. Fatima Zahra Harmouch & Ahmed F. Ebrahim & Mohammad Mahmoudian Esfahani & Nissrine Krami & Nabil Hmina & Osama A. Mohammed, 2019. "An Optimal Energy Management System for Real-Time Operation of Multiagent-Based Microgrids Using a T-Cell Algorithm," Energies, MDPI, vol. 12(15), pages 1-23, August.
    7. Muhammad Salman Sami & Muhammad Abrar & Rizwan Akram & Muhammad Majid Hussain & Mian Hammad Nazir & Muhammad Saad Khan & Safdar Raza, 2021. "Energy Management of Microgrids for Smart Cities: A Review," Energies, MDPI, vol. 14(18), pages 1-18, September.
    8. Hao, Ran & Lu, Tianguang & Ai, Qian & Wang, Zhe & Wang, Xiaolong, 2020. "Distributed online learning and dynamic robust standby dispatch for networked microgrids," Applied Energy, Elsevier, vol. 274(C).
    9. Marek Krok & Paweł Majewski & Wojciech P. Hunek & Tomasz Feliks, 2022. "Energy Optimization of the Continuous-Time Perfect Control Algorithm," Energies, MDPI, vol. 15(4), pages 1-13, February.
    10. Beigvand, Soheil Derafshi & Abdi, Hamdi & La Scala, Massimo, 2017. "A general model for energy hub economic dispatch," Applied Energy, Elsevier, vol. 190(C), pages 1090-1111.
    11. El-Sharafy, M. Zaki & Farag, Hany E.Z., 2017. "Back-feed power restoration using distributed constraint optimization in smart distribution grids clustered into microgrids," Applied Energy, Elsevier, vol. 206(C), pages 1102-1117.
    12. Clarke, Will Challis & Brear, Michael John & Manzie, Chris, 2020. "Control of an isolated microgrid using hierarchical economic model predictive control," Applied Energy, Elsevier, vol. 280(C).
    13. Korkas, Christos D. & Baldi, Simone & Michailidis, Iakovos & Kosmatopoulos, Elias B., 2015. "Intelligent energy and thermal comfort management in grid-connected microgrids with heterogeneous occupancy schedule," Applied Energy, Elsevier, vol. 149(C), pages 194-203.
    14. Mazzola, Simone & Astolfi, Marco & Macchi, Ennio, 2015. "A detailed model for the optimal management of a multigood microgrid," Applied Energy, Elsevier, vol. 154(C), pages 862-873.
    15. Panda, Debashish & Ramteke, Manojkumar, 2019. "Preventive crude oil scheduling under demand uncertainty using structure adapted genetic algorithm," Applied Energy, Elsevier, vol. 235(C), pages 68-82.
    16. Ali Hadi Abdulwahid & Shaorong Wang, 2016. "A Novel Approach for Microgrid Protection Based upon Combined ANFIS and Hilbert Space-Based Power Setting," Energies, MDPI, vol. 9(12), pages 1-25, December.
    17. Gonzalez de Durana, Jose & Barambones, Oscar, 2018. "Technology-free microgrid modeling with application to demand side management," Applied Energy, Elsevier, vol. 219(C), pages 165-178.
    18. Qingwu Gong & Jiazhi Lei & Jun Ye, 2016. "Optimal Siting and Sizing of Distributed Generators in Distribution Systems Considering Cost of Operation Risk," Energies, MDPI, vol. 9(1), pages 1-18, January.
    19. Giaouris, Damian & Papadopoulos, Athanasios I. & Patsios, Charalampos & Walker, Sara & Ziogou, Chrysovalantou & Taylor, Phil & Voutetakis, Spyros & Papadopoulou, Simira & Seferlis, Panos, 2018. "A systems approach for management of microgrids considering multiple energy carriers, stochastic loads, forecasting and demand side response," Applied Energy, Elsevier, vol. 226(C), pages 546-559.
    20. Hossein Shayeghi & Elnaz Shahryari & Mohammad Moradzadeh & Pierluigi Siano, 2019. "A Survey on Microgrid Energy Management Considering Flexible Energy Sources," Energies, MDPI, vol. 12(11), pages 1-26, June.

    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:174:y:2019:i:c:p:576-590. 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.