IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i13p2275-d851278.html
   My bibliography  Save this article

A Multi-Agent Approach for Self-Healing and RES-Penetration in Smart Distribution Networks

Author

Listed:
  • Ahmed Maged Abdelhamid

    (Engineering Consultants Group S. A. (ECG), Alexandria 21532, Egypt)

  • Nahla E. Zakzouk

    (Electrical and Control Engineering Department, College of Engineering and Technology, Arab Academy for Science and Technology (AAST), Abu-Kir Campus, Alexandria 1029, Egypt)

  • Samah El Safty

    (Electrical and Control Engineering Department, College of Engineering and Technology, Arab Academy for Science and Technology (AAST), Abu-Kir Campus, Alexandria 1029, Egypt)

Abstract

Smart grid technology has gained much consideration recently to make use of intelligent control in the automatic fault-detection and self-healing of electric networks. This ensures a reliable electricity supply and an efficient operation of the distribution system against disasters with minimum human interaction. In this paper, a fully decentralized multi-agent system (MAS) algorithm, for self-healing in smart distribution systems, is proposed. The novelty of the proposed algorithm, compared to related work, is its ability to combine the zone and feeder agents, specified for system self-healing, with micro-grid agents. This enables the system to successfully achieve functions of fault locating and isolation along with service-restoration using expert rules while considering both operational constraint and load priorities. Meanwhile, managing the power flow and controlling the distributed generator (DG) contribution, in the considered network, is a bonus merit for the proposed algorithm. Hence, system self-healing as well as strengthening energy security and resiliency are guaranteed. The proposed algorithm is tested on a 22 kV radial distribution system through several case-studies with/without a DG wind-energy source. The employed agents are implemented in the Java Agent Developing Framework (JADE) environment to communicate and make decisions. Power system simulation and calculations are carried out in MATLAB to validate the agents’ decisions.

Suggested Citation

  • Ahmed Maged Abdelhamid & Nahla E. Zakzouk & Samah El Safty, 2022. "A Multi-Agent Approach for Self-Healing and RES-Penetration in Smart Distribution Networks," Mathematics, MDPI, vol. 10(13), pages 1-26, June.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:13:p:2275-:d:851278
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/13/2275/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/13/2275/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Martin-Martínez, F. & Sánchez-Miralles, A. & Rivier, M., 2016. "A literature review of Microgrids: A functional layer based classification," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 1133-1153.
    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. Zhang, Pan & Mansouri, Seyed Amir & Rezaee Jordehi, Ahmad & Tostado-Véliz, Marcos & Alharthi, Yahya Z. & Safaraliev, Murodbek, 2024. "An ADMM-enabled robust optimization framework for self-healing scheduling of smart grids integrated with smart prosumers," Applied Energy, Elsevier, vol. 363(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. Hirsch, Adam & Parag, Yael & Guerrero, Josep, 2018. "Microgrids: A review of technologies, key drivers, and outstanding issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 402-411.
    2. Calvillo, C.F. & Sánchez-Miralles, A. & Villar, J. & Martín, F., 2016. "Optimal planning and operation of aggregated distributed energy resources with market participation," Applied Energy, Elsevier, vol. 182(C), pages 340-357.
    3. Miguel Carpintero-Rentería & David Santos-Martín & Josep M. Guerrero, 2019. "Microgrids Literature Review through a Layers Structure," Energies, MDPI, vol. 12(22), pages 1-22, November.
    4. Fridgen, Gilbert & Kahlen, Micha & Ketter, Wolfgang & Rieger, Alexander & Thimmel, Markus, 2018. "One rate does not fit all: An empirical analysis of electricity tariffs for residential microgrids," Applied Energy, Elsevier, vol. 210(C), pages 800-814.
    5. Matthew Gough & Sérgio F. Santos & Mohammed Javadi & Rui Castro & João P. S. Catalão, 2020. "Prosumer Flexibility: A Comprehensive State-of-the-Art Review and Scientometric Analysis," Energies, MDPI, vol. 13(11), pages 1-32, May.
    6. Milis, Kevin & Peremans, Herbert & Van Passel, Steven, 2018. "The impact of policy on microgrid economics: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 3111-3119.
    7. Isaías González & Antonio José Calderón & José María Portalo, 2021. "Innovative Multi-Layered Architecture for Heterogeneous Automation and Monitoring Systems: Application Case of a Photovoltaic Smart Microgrid," Sustainability, MDPI, vol. 13(4), pages 1-24, February.
    8. Linda Barelli & Gianni Bidini & Fabio Bonucci & Luca Castellini & Simone Castellini & Andrea Ottaviano & Dario Pelosi & Alberto Zuccari, 2018. "Dynamic Analysis of a Hybrid Energy Storage System (H-ESS) Coupled to a Photovoltaic (PV) Plant," Energies, MDPI, vol. 11(2), pages 1-23, February.
    9. Lenhart, Stephanie & Araújo, Kathleen, 2021. "Microgrid decision-making by public power utilities in the United States: A critical assessment of adoption and technological profiles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    10. Nelson, James & Johnson, Nathan G. & Fahy, Kelsey & Hansen, Timothy A., 2020. "Statistical development of microgrid resilience during islanding operations," Applied Energy, Elsevier, vol. 279(C).
    11. Warneryd, Martin & Håkansson, Maria & Karltorp, Kersti, 2020. "Unpacking the complexity of community microgrids: A review of institutions’ roles for development of microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 121(C).
    12. Jose R Sicchar & Carlos T. Da Costa & Jose R. Silva & Raimundo C. Oliveira & Werbeston D. Oliveira, 2018. "A Load-Balance System Design of Microgrid Cluster Based on Hierarchical Petri Nets," Energies, MDPI, vol. 11(12), pages 1-30, November.
    13. Mengelkamp, Esther & Schlund, David & Weinhardt, Christof, 2019. "Development and real-world application of a taxonomy for business models in local energy markets," Applied Energy, Elsevier, vol. 256(C).
    14. Martín-Martínez, F. & Sánchez-Miralles, A. & Rivier, M. & Calvillo, C.F., 2017. "Centralized vs distributed generation. A model to assess the relevance of some thermal and electric factors. Application to the Spanish case study," Energy, Elsevier, vol. 134(C), pages 850-863.
    15. Kanakadhurga, Dharmaraj & Prabaharan, Natarajan, 2022. "Demand side management in microgrid: A critical review of key issues and recent trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    16. Ferahtia, Seydali & Houari, Azeddine & Cioara, Tudor & Bouznit, Mohammed & Rezk, Hegazy & Djerioui, Ali, 2024. "Recent advances on energy management and control of direct current microgrid for smart cities and industry: A Survey," Applied Energy, Elsevier, vol. 368(C).
    17. Milis, Kevin & Peremans, Herbert & Van Passel, Steven, 2018. "Steering the adoption of battery storage through electricity tariff design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 125-139.
    18. Tabar, Vahid Sohrabi & Jirdehi, Mehdi Ahmadi & Hemmati, Reza, 2017. "Energy management in microgrid based on the multi objective stochastic programming incorporating portable renewable energy resource as demand response option," Energy, Elsevier, vol. 118(C), pages 827-839.
    19. Cagnano, A. & De Tuglie, E. & Mancarella, P., 2020. "Microgrids: Overview and guidelines for practical implementations and operation," Applied Energy, Elsevier, vol. 258(C).
    20. Alfred Benedikt Brendel & Friedrich Chasin & Milad Mirbabaie & Dennis M. Riehle & Christine Harnischmacher, 2022. "Review of Design-Oriented Green Information Systems Research," Sustainability, MDPI, vol. 14(8), pages 1-33, April.

    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:jmathe:v:10:y:2022:i:13:p:2275-:d:851278. 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.