IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i6p2598-d1092610.html
   My bibliography  Save this article

Cooperative Game-Based Collaborative Optimal Regulation-Assisted Digital Twins for Wide-Area Distributed Energy

Author

Listed:
  • Pengcheng Ni

    (Anhui Jiyuan Software Co., Ltd., Hefei 230000, China)

  • Zhiyuan Ye

    (Anhui Jiyuan Software Co., Ltd., Hefei 230000, China)

  • Can Cao

    (Anhui Jiyuan Software Co., Ltd., Hefei 230000, China)

  • Zhimin Guo

    (State Grid Henan Electric Power Research Institute, Zhengzhou 450000, China)

  • Jian Zhao

    (State Grid Henan Electric Power Research Institute, Zhengzhou 450000, China)

  • Xing He

    (School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)

Abstract

With the wide use of renewable energy sources and the requirement for energy storage technology, the field of power systems is facing the need for further technological innovation. This paper proposes a wide-area distributed energy model based on digital twins. This model was constructed to more fully optimize the coordination of wide-area distributed energy in order to rationally deploy and utilize new energy units. Moreover, the minimization of the power deviation between the dispatch command and the actual power regulation output was also taken into account. In contrast to previous dispatch research, the cooperative game co-optimization algorithm was applied to this model, enabling a distributed approach that can quickly obtain a high-quality power command scheduling scheme. Finally, the simulation and comparison experiments using this algorithm with the wide-area distributed energy (WDE) model showed that it had the advantages of significantly reducing the tracking error, average error, and total error and effectively improving the tracking accuracy. The proposed method can help reduce total power deviations by about 61.1%, 55.7%, 53.1%, and 74.8%.

Suggested Citation

  • Pengcheng Ni & Zhiyuan Ye & Can Cao & Zhimin Guo & Jian Zhao & Xing He, 2023. "Cooperative Game-Based Collaborative Optimal Regulation-Assisted Digital Twins for Wide-Area Distributed Energy," Energies, MDPI, vol. 16(6), pages 1-17, March.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:6:p:2598-:d:1092610
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/6/2598/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/6/2598/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ivan Smajla & Daria Karasalihović Sedlar & Branko Drljača & Lucija Jukić, 2019. "Fuel Switch to LNG in Heavy Truck Traffic," Energies, MDPI, vol. 12(3), pages 1-19, February.
    2. Zhang, Xiaoshun & Yu, Tao & Yang, Bo & Li, Li, 2016. "Virtual generation tribe based robust collaborative consensus algorithm for dynamic generation command dispatch optimization of smart grid," Energy, Elsevier, vol. 101(C), pages 34-51.
    3. Michael W. Grieves, 2005. "Product lifecycle management: the new paradigm for enterprises," International Journal of Product Development, Inderscience Enterprises Ltd, vol. 2(1/2), pages 71-84.
    4. Tingyi He & Shengnan Li & Shuijun Wu & Chuangzhi Li & Biao Xu, 2021. "Biobjective Optimization-Based Frequency Regulation of Power Grids with High-Participated Renewable Energy and Energy Storage Systems," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-16, March.
    5. Li, Jiawen & Yu, Tao & Zhang, Xiaoshun & Li, Fusheng & Lin, Dan & Zhu, Hanxin, 2021. "Efficient experience replay based deep deterministic policy gradient for AGC dispatch in integrated energy system," Applied Energy, Elsevier, vol. 285(C).
    6. Mohammadhafez Bazrafshan & Likhitha Yalamanchili & Nikolaos Gatsis & Juan Gomez, 2019. "Stochastic Planning of Distributed PV Generation," Energies, MDPI, vol. 12(3), pages 1-20, January.
    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. Quan, Yue & Xi, Lei, 2024. "Smart generation system: A decentralized multi-agent control architecture based on improved consensus algorithm for generation command dispatch of sustainable energy systems," Applied Energy, Elsevier, vol. 365(C).
    2. Johannes Full & Silja Hohmann & Sonja Ziehn & Edgar Gamero & Tobias Schließ & Hans-Peter Schmid & Robert Miehe & Alexander Sauer, 2023. "Perspectives of Biogas Plants as BECCS Facilities: A Comparative Analysis of Biomethane vs. Biohydrogen Production with Carbon Capture and Storage or Use (CCS/CCU)," Energies, MDPI, vol. 16(13), pages 1-16, June.
    3. Maria Mercanti-Guérin, 2021. "From Perceived Creativity To Status Quo Bias The Case Of Digital Twins In The Home," Post-Print hal-03450262, HAL.
    4. Chen, Ziyue & Huang, Lizhen, 2021. "Digital twins for information-sharing in remanufacturing supply chain: A review," Energy, Elsevier, vol. 220(C).
    5. Hassan Alimam & Giovanni Mazzuto & Marco Ortenzi & Filippo Emanuele Ciarapica & Maurizio Bevilacqua, 2023. "Intelligent Retrofitting Paradigm for Conventional Machines towards the Digital Triplet Hierarchy," Sustainability, MDPI, vol. 15(2), pages 1-30, January.
    6. Kumar Jadoun, Vinay & Rahul Prashanth, G & Suhas Joshi, Siddharth & Narayanan, K. & Malik, Hasmat & García Márquez, Fausto Pedro, 2022. "Optimal fuzzy based economic emission dispatch of combined heat and power units using dynamically controlled Whale Optimization Algorithm," Applied Energy, Elsevier, vol. 315(C).
    7. Xi, Lei & Shi, Yu & Quan, Yue & Liu, Zhihong, 2024. "Research on the multi-area cooperative control method for novel power systems," Energy, Elsevier, vol. 313(C).
    8. Zhu, Ziqing & Hu, Ze & Chan, Ka Wing & Bu, Siqi & Zhou, Bin & Xia, Shiwei, 2023. "Reinforcement learning in deregulated energy market: A comprehensive review," Applied Energy, Elsevier, vol. 329(C).
    9. Krzysztof Biernat & Izabela Samson-Bręk & Zdzisław Chłopek & Marlena Owczuk & Anna Matuszewska, 2021. "Assessment of the Environmental Impact of Using Methane Fuels to Supply Internal Combustion Engines," Energies, MDPI, vol. 14(11), pages 1-19, June.
    10. F. H. Abanda & N. Jian & S. Adukpo & V. V. Tuhaise & M. B. Manjia, 2025. "Digital twin for product versus project lifecycles’ development in manufacturing and construction industries," Journal of Intelligent Manufacturing, Springer, vol. 36(2), pages 801-831, February.
    11. Li, Jiawen & Zhou, Tao, 2023. "Active fault-tolerant coordination energy management for a proton exchange membrane fuel cell using curriculum-based multiagent deep meta-reinforcement learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).
    12. Wang, Jinrui & Zhang, Zongzhen & Liu, Zhiliang & Han, Baokun & Bao, Huaiqian & Ji, Shanshan, 2023. "Digital twin aided adversarial transfer learning method for domain adaptation fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    13. Lu, Xin & Qiu, Jing & Zhang, Cuo & Lei, Gang & Zhu, Jianguo, 2024. "Seizing unconventional arbitrage opportunities in virtual power plants: A profitable and flexible recruitment approach," Applied Energy, Elsevier, vol. 358(C).
    14. Verdouw, Cor & Tekinerdogan, Bedir & Beulens, Adrie & Wolfert, Sjaak, 2021. "Digital twins in smart farming," Agricultural Systems, Elsevier, vol. 189(C).
    15. Sayed, Aya Nabil & Himeur, Yassine & Varlamis, Iraklis & Bensaali, Faycal, 2025. "Continual learning for energy management systems: A review of methods and applications, and a case study," Applied Energy, Elsevier, vol. 384(C).
    16. Assunta Di Vaio & Sabrina Palladino & Elisa Van Engelenhoven, 2025. "Digital Twins nei Sistemi Portuali e il contributo di GHG accounting: Una review della letteratura," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2025(1), pages 211-236.
    17. Yin, Linfei & Li, Yu, 2022. "Hybrid multi-agent emotional deep Q network for generation control of multi-area integrated energy systems," Applied Energy, Elsevier, vol. 324(C).
    18. Han, Ji & Zhang, Di & Jia, Bohui & Xie, Longjie & Wan, Weijia & Tan, Junyang & Chen, Zhe, 2025. "Power loss minimization-oriented reactive power control for wind farm equipped with distributed energy storages using clustering-based data-driven method," Energy, Elsevier, vol. 328(C).
    19. Qu, Kaiping & Yu, Tao & Huang, Linni & Yang, Bo & Zhang, Xiaoshun, 2018. "Decentralized optimal multi-energy flow of large-scale integrated energy systems in a carbon trading market," Energy, Elsevier, vol. 149(C), pages 779-791.
    20. Dianyou Yu & Zheng He, 2022. "Digital twin-driven intelligence disaster prevention and mitigation for infrastructure: advances, challenges, and opportunities," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(1), pages 1-36, May.

    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:16:y:2023:i:6:p:2598-:d:1092610. 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.