IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i16p4423-d1727770.html

Binary Grey Wolf Optimization Algorithm-Based Load Scheduling Using a Multi-Agent System in a Grid-Tied Solar Microgrid

Author

Listed:
  • Sujo Vasu

    (Department of Electrical and Electronics Engineering, Government Engineering College Thrissur, Affiliated to A P J Abdul Kalam Technological University, Thiruvananthapuram 695016, India)

  • P Ramesh Kumar

    (Department of Electrical and Electronics Engineering, Government Engineering College Wayanad, Affiliated to A P J Abdul Kalam Technological University, Thiruvananthapuram 695016, India
    These authors contributed equally to this work.)

  • E A Jasmin

    (Department of Electrical and Electronics Engineering, Government Engineering College Kozhikode, Affiliated to A P J Abdul Kalam Technological University, Thiruvananthapuram 695016, India
    These authors contributed equally to this work.)

Abstract

Microgrids play a crucial role in the development of future smart grids, with multiple interconnected microgrids forming large-scale multi-microgrid systems that operate as smart grids. Multi-agent system (MAS)-based control solutions are the most suitable for addressing such control challenges. This paper presents a demand-side management (DSM) strategy using a meta-heuristic optimization technique for minimizing the household energy consumption cost using MAS. The binary grey wolf optimization algorithm (BGWOA) optimizes load scheduling, reducing electricity costs, without compromising consumer preferences using time-of-day (ToD) tariffs. The communication agents and load agents comprise the MAS used to streamline load control operations. The results demonstrate that MAS-based load control using metaheuristic optimization techniques enhances demand-side management, thus minimizing the electricity costs while adhering to contradictory parameters like user preferences, appliance duration, and load atomicity. This makes renewable energy integration more cost-effective in smart grids, thereby ensuring affordable, reliable, and sustainable energy for all.

Suggested Citation

  • Sujo Vasu & P Ramesh Kumar & E A Jasmin, 2025. "Binary Grey Wolf Optimization Algorithm-Based Load Scheduling Using a Multi-Agent System in a Grid-Tied Solar Microgrid," Energies, MDPI, vol. 18(16), pages 1-27, August.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:16:p:4423-:d:1727770
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/16/4423/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/18/16/4423/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hussein Jumma Jabir & Jiashen Teh & Dahaman Ishak & Hamza Abunima, 2018. "Impacts of Demand-Side Management on Electrical Power Systems: A Review," Energies, MDPI, vol. 11(5), pages 1-19, April.
    2. Mbungu, Nsilulu T. & Bansal, Ramesh C. & Naidoo, Raj M. & Bettayeb, Maamar & Siti, Mukwanga W. & Bipath, Minnesh, 2020. "A dynamic energy management system using smart metering," Applied Energy, Elsevier, vol. 280(C).
    3. Wang, Can & Wang, Mingchao & Wang, Aoqi & Zhang, Xiaojia & Zhang, Jiaheng & Ma, Hui & Yang, Nan & Zhao, Zhuoli & Lai, Chun Sing & Lai, Loi Lei, 2025. "Multiagent deep reinforcement learning-based cooperative optimal operation with strong scalability for residential microgrid clusters," Energy, Elsevier, vol. 314(C).
    4. Strbac, Goran, 2008. "Demand side management: Benefits and challenges," Energy Policy, Elsevier, vol. 36(12), pages 4419-4426, December.
    5. Wang, Can & Zhang, Jiaheng & Wang, Aoqi & Wang, Zhen & Yang, Nan & Zhao, Zhuoli & Lai, Chun Sing & Lai, Loi Lei, 2024. "Prioritized sum-tree experience replay TD3 DRL-based online energy management of a residential microgrid," Applied Energy, Elsevier, vol. 368(C).
    6. Zdenek Bradac & Vaclav Kaczmarczyk & Petr Fiedler, 2014. "Optimal Scheduling of Domestic Appliances via MILP," Energies, MDPI, vol. 8(1), pages 1-16, December.
    7. Pingliang Zeng & Jin Xu & Minchen Zhu, 2024. "Demand Response Strategy Based on the Multi-Agent System and Multiple-Load Participation," Sustainability, MDPI, vol. 16(2), pages 1-21, January.
    8. Ibrahim Alotaibi & Mohammed A. Abido & Muhammad Khalid & Andrey V. Savkin, 2020. "A Comprehensive Review of Recent Advances in Smart Grids: A Sustainable Future with Renewable Energy Resources," Energies, MDPI, vol. 13(23), pages 1-41, November.
    Full references (including those not matched with items on IDEAS)

    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. Chen-Yu Chang & Pei-Fang Tsai, 2022. "Multiobjective Decision-Making Model for Power Scheduling Problem in Smart Homes," Sustainability, MDPI, vol. 14(19), pages 1-13, September.
    2. Maria Symeonidou & Agis M. Papadopoulos, 2022. "Selection and Dimensioning of Energy Storage Systems for Standalone Communities: A Review," Energies, MDPI, vol. 15(22), pages 1-28, November.
    3. Navid Rezaei & Abdollah Ahmadi & Mohammadhossein Deihimi, 2022. "A Comprehensive Review of Demand-Side Management Based on Analysis of Productivity: Techniques and Applications," Energies, MDPI, vol. 15(20), pages 1-28, October.
    4. Roy, Anthony & Auger, François & Dupriez-Robin, Florian & Bourguet, Salvy & Tran, Quoc Tuan, 2020. "A multi-level Demand-Side Management algorithm for offgrid multi-source systems," Energy, Elsevier, vol. 191(C).
    5. Wang, Can & Liu, Yuzheng & Zhang, Yu & Xi, Lei & Yang, Nan & Zhao, Zhuoli & Lai, Chun Sing & Lai, Loi Lei, 2025. "Strategy for optimizing the bidirectional time-of-use electricity price in multi-microgrids coupled with multilevel games," Energy, Elsevier, vol. 323(C).
    6. Cheng, Meng & Sami, Saif Sabah & Wu, Jianzhong, 2017. "Benefits of using virtual energy storage system for power system frequency response," Applied Energy, Elsevier, vol. 194(C), pages 376-385.
    7. McPherson, Madeleine & Stoll, Brady, 2020. "Demand response for variable renewable energy integration: A proposed approach and its impacts," Energy, Elsevier, vol. 197(C).
    8. Daví-Arderius, Daniel & Sanin, María-Eugenia & Trujillo-Baute, Elisa, 2017. "CO2 content of electricity losses," Energy Policy, Elsevier, vol. 104(C), pages 439-445.
    9. Schachter, Jonathan A. & Mancarella, Pierluigi & Moriarty, John & Shaw, Rita, 2016. "Flexible investment under uncertainty in smart distribution networks with demand side response: Assessment framework and practical implementation," Energy Policy, Elsevier, vol. 97(C), pages 439-449.
    10. Bernadeta Gołębiowska & Anna Bartczak & Mikołaj Czajkowski, 2020. "Energy Demand Management and Social Norms," Energies, MDPI, vol. 13(15), pages 1-20, July.
    11. Abdul K Hamid & Nsilulu T Mbungu & A. Elnady & Ramesh C Bansal & Ali A Ismail & Mohammad A AlShabi, 2023. "A systematic review of grid-connected photovoltaic and photovoltaic/thermal systems: Benefits, challenges and mitigation," Energy & Environment, , vol. 34(7), pages 2775-2814, November.
    12. Hafize Nurgul Durmus Senyapar & Ramazan Bayindir, 2023. "The Research Agenda on Smart Grids: Foresights for Social Acceptance," Energies, MDPI, vol. 16(18), pages 1-31, September.
    13. Wadim Strielkowski & Dalia Streimikiene & Alena Fomina & Elena Semenova, 2019. "Internet of Energy (IoE) and High-Renewables Electricity System Market Design," Energies, MDPI, vol. 12(24), pages 1-17, December.
    14. Arjuna Nebel & Christine Krüger & Tomke Janßen & Mathieu Saurat & Sebastian Kiefer & Karin Arnold, 2020. "Comparison of the Effects of Industrial Demand Side Management and Other Flexibilities on the Performance of the Energy System," Energies, MDPI, vol. 13(17), pages 1-20, August.
    15. Kokou Amega & Yendoubé Laré & Ramchandra Bhandari & Yacouba Moumouni & Aklesso Y. G. Egbendewe & Windmanagda Sawadogo & Saidou Madougou, 2022. "Solar Energy Powered Decentralized Smart-Grid for Sustainable Energy Supply in Low-Income Countries: Analysis Considering Climate Change Influences in Togo," Energies, MDPI, vol. 15(24), pages 1-24, December.
    16. Nolan, Sheila & Neu, Olivier & O’Malley, Mark, 2017. "Capacity value estimation of a load-shifting resource using a coupled building and power system model," Applied Energy, Elsevier, vol. 192(C), pages 71-82.
    17. Llaria, Alvaro & Curea, Octavian & Jiménez, Jaime & Camblong, Haritza, 2011. "Survey on microgrids: Unplanned islanding and related inverter control techniques," Renewable Energy, Elsevier, vol. 36(8), pages 2052-2061.
    18. Katz, Jonas, 2014. "Linking meters and markets: Roles and incentives to support a flexible demand side," Utilities Policy, Elsevier, vol. 31(C), pages 74-84.
    19. Busiswe Skosana & Mukwanga W. Siti & Nsilulu T. Mbungu & Sonu Kumar & Willy Mulumba, 2023. "An Evaluation of Potential Strategies in Renewable Energy Systems and Their Importance for South Africa—A Review," Energies, MDPI, vol. 16(22), pages 1-27, November.
    20. Saheb Khanabdal & Mahdi Banejad & Frede Blaabjerg & Nasser Hosseinzadeh, 2021. "A Novel Power Sharing Strategy Based on Virtual Flux Droop and Model Predictive Control for Islanded Low-Voltage AC Microgrids," Energies, MDPI, vol. 14(16), pages 1-17, August.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:18:y:2025:i:16:p:4423-:d:1727770. 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 The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address (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.