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Real-Time Framework for Energy Management System of a Smart Microgrid Using Multiagent Systems

Author

Listed:
  • Roberto S. Netto

    (Institute of Electrical Systems and Energy, Federal University of Itajuba, Itajuba MG 37500-903, Brazil)

  • Guilherme R. Ramalho

    (Instituto Federal Sul de Minas Gerais, Poços de Caldas MG 37713-100, Brazil)

  • Benedito D. Bonatto

    (Institute of Electrical Systems and Energy, Federal University of Itajuba, Itajuba MG 37500-903, Brazil)

  • Otavio A. S. Carpinteiro

    (Institute of System Engineering and Information Tecnology, Federal University of Itajuba, Itajuba MG 37500-903, Brazil)

  • A. C. Zambroni de Souza

    (Institute of Electrical Systems and Energy, Federal University of Itajuba, Itajuba MG 37500-903, Brazil)

  • Denisson Q. Oliveira

    (Department of Computer Engineering, Federal University of Maranhão, São Luís MA 65080-805, Brazil)

  • Rodrigo A. S. Braga

    (Institute of System Engineering and Information Tecnology, Federal University of Itajuba, Itajuba MG 37500-903, Brazil)

Abstract

This paper presents a framework to analyze the problem of real-time management of Smart Grids. For this purpose, the energy management is integrated with the power system through a telecommunication system. The use of Multiagent Systems (MAS) leads the proposed algorithm to find the best-integrated solution, taking into consideration the operating scenario and the system characteristics. With this framework it was possible to evaluate the design of the energy management and the impact of the algorithm developed in the MAS. In the same way, the data sent from the power system to be used for energy management have a direct impact on his behavior. The proposed framework is tested with the help of a microgrid, so the results may be replicated.

Suggested Citation

  • Roberto S. Netto & Guilherme R. Ramalho & Benedito D. Bonatto & Otavio A. S. Carpinteiro & A. C. Zambroni de Souza & Denisson Q. Oliveira & Rodrigo A. S. Braga, 2018. "Real-Time Framework for Energy Management System of a Smart Microgrid Using Multiagent Systems," Energies, MDPI, vol. 11(3), pages 1-17, March.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:3:p:656-:d:136369
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    References listed on IDEAS

    as
    1. Bakar, Nur Najihah Abu & Hassan, Mohammad Yusri & Sulaima, Mohamad Fani & Mohd Nasir, Mohamad Na’im & Khamis, Aziah, 2017. "Microgrid and load shedding scheme during islanded mode: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 161-169.
    2. Moradi, Mohammad H. & Razini, Saleh & Mahdi Hosseinian, S., 2016. "State of art of multiagent systems in power engineering: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 814-824.
    3. 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.
    4. Morais, Hugo & Kádár, Péter & Faria, Pedro & Vale, Zita A. & Khodr, H.M., 2010. "Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming," Renewable Energy, Elsevier, vol. 35(1), pages 151-156.
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    Cited by:

    1. Giovanni Mercurio Casolino & Mario Russo & Pietro Varilone & Daniele Pescosolido, 2018. "Hardware-in-the-Loop Validation of Energy Management Systems for Microgrids: A Short Overview and a Case Study," Energies, MDPI, vol. 11(11), pages 1-17, November.
    2. Joanna Kott & Marek Kott, 2019. "Generic Ontology of Energy Consumption Households," Energies, MDPI, vol. 12(19), pages 1-19, September.
    3. 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.

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