IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v318y2025ics0360544225004335.html
   My bibliography  Save this article

A day-ahead self-dispatch optimization framework for load-side virtual control units participating in active power regulation of power grids

Author

Listed:
  • Zhang, Mingze
  • Li, Weidong
  • Yu, Samson S.
  • Li, Haomin
  • Lv, Yanling
  • Shen, Jiakai

Abstract

Distributed flexible resources on the load side of power systems can be aggregated into virtual control units (VCUs), which are directly dispatched by bulk power grids to participate in active power regulation at the distribution-grid level. However, existing dispatch methods fail to address the self-dispatch optimization challenges for fully-controllable and semi-controllable resources aggregated as VCUs, limiting the potential of load-side resources in the daily full-timescale frequency control ancillary services (FCASs). This study proposes aggregating electric vehicle (EV) battery swapping and charging stations (BSCSs) and small-scale battery energy storage stations (BESSs) into VCUs. To optimize the sequential strategies of these VCUs in responding to full timescale FCAS tasks in the day-ahead stage, two self-dispatch optimization frameworks are developed for the two forms of VCUs. A novel VCU operational mechanism is designed to ensure optimal coordination of multiple tasks by capturing the dynamic and time-varying regulation capabilities of distributed resources. To enhance the coordination of various flexible resources, the proposed framework introduces intra-station self-sufficiency and inter-station mutual aid as operational modes. Case studies for the two VCU configurations demonstrate the effectiveness of the approach. The results show that the VCUs can effectively evaluate and implement optimized allocation strategies allocation for grid dispatch tasks, balancing resource utilization between BESS clusters and BSCSs while accommodating the stochastic EV swapping demands faced by BSCSs.

Suggested Citation

  • Zhang, Mingze & Li, Weidong & Yu, Samson S. & Li, Haomin & Lv, Yanling & Shen, Jiakai, 2025. "A day-ahead self-dispatch optimization framework for load-side virtual control units participating in active power regulation of power grids," Energy, Elsevier, vol. 318(C).
  • Handle: RePEc:eee:energy:v:318:y:2025:i:c:s0360544225004335
    DOI: 10.1016/j.energy.2025.134791
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544225004335
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2025.134791?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Zhang, Mingze & Li, Weidong & Yu, Samson Shenglong & Wang, Haixia & Ba, Yu, 2024. "Optimal day-ahead large-scale battery dispatch model for multi-regulation participation considering full timescale uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    2. Lund, Henrik & Andersen, Anders N. & Østergaard, Poul Alberg & Mathiesen, Brian Vad & Connolly, David, 2012. "From electricity smart grids to smart energy systems – A market operation based approach and understanding," Energy, Elsevier, vol. 42(1), pages 96-102.
    3. Li, Xinyan & Wu, Nan, 2024. "A two-stage distributed robust optimal control strategy for energy collaboration in multi-regional integrated energy systems based on cooperative game," Energy, Elsevier, vol. 305(C).
    4. Yuan, Meng & Sorknæs, Peter & Lund, Henrik & Liang, Yongtu, 2022. "The bidding strategies of large-scale battery storage in 100% renewable smart energy systems," Applied Energy, Elsevier, vol. 326(C).
    5. Pandey, Anubhav Kumar & Jadoun, Vinay Kumar & Jayalakshmi, N.S. & Malik, Hasmat & García Márquez, Fausto Pedro, 2024. "Multi-objective price based flexible reserve scheduling of virtual power plant," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    6. Zhang, Mingze & Li, Weidong & Yu, Samson Shenglong & Wen, Kerui & Muyeen, S.M., 2023. "Day-ahead optimization dispatch strategy for large-scale battery energy storage considering multiple regulation and prediction failures," Energy, Elsevier, vol. 270(C).
    7. Srivastava, Mahima & Tiwari, Prashant Kumar, 2024. "A profit driven optimal scheduling of virtual power plants for peak load demand in competitive electricity markets with machine learning based forecasted generations," Energy, Elsevier, vol. 310(C).
    8. Son, Yeong Geon & Kim, Sung Yul, 2024. "Optimal planning and operation of integrated energy systems in South Korea: Introducing a Novel ambiguity set based distributionally robust optimization," Energy, Elsevier, vol. 307(C).
    9. Xie, Rui & Wei, Wei & Li, Mingxuan & Dong, ZhaoYang & Mei, Shengwei, 2023. "Sizing capacities of renewable generation, transmission, and energy storage for low-carbon power systems: A distributionally robust optimization approach," Energy, Elsevier, vol. 263(PA).
    10. Zhang, Mingze & Li, Weidong & Yu, Samson Shenglong & Wen, Kerui & Zhou, Chen & Shi, Peng, 2021. "A unified configurational optimization framework for battery swapping and charging stations considering electric vehicle uncertainty," Energy, Elsevier, vol. 218(C).
    11. Li, Jinchao & Sun, Zihao & Niu, Xiaoxuan & Li, Shiwei, 2024. "Economic optimization scheduling of virtual power plants considering an incentive based tiered carbon price," Energy, Elsevier, vol. 305(C).
    12. Cui, Dingsong & Wang, Zhenpo & Liu, Peng & Wang, Shuo & Dorrell, David G. & Li, Xiaohui & Zhan, Weipeng, 2023. "Operation optimization approaches of electric vehicle battery swapping and charging station: A literature review," Energy, Elsevier, vol. 263(PE).
    13. Bhuiyan, Erphan A. & Hossain, Md. Zahid & Muyeen, S.M. & Fahim, Shahriar Rahman & Sarker, Subrata K. & Das, Sajal K., 2021. "Towards next generation virtual power plant: Technology review and frameworks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    14. Makolo, Peter & Zamora, Ramon & Lie, Tek-Tjing, 2021. "The role of inertia for grid flexibility under high penetration of variable renewables - A review of challenges and solutions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    15. Dimitris Bertsimas & Aurélie Thiele, 2006. "A Robust Optimization Approach to Inventory Theory," Operations Research, INFORMS, vol. 54(1), pages 150-168, February.
    16. Zhou, Kaile & Peng, Ning & Yin, Hui & Hu, Rong, 2023. "Urban virtual power plant operation optimization with incentive-based demand response," Energy, Elsevier, vol. 282(C).
    17. Chang, Weiguang & Yang, Qiang, 2023. "Low carbon oriented collaborative energy management framework for multi-microgrid aggregated virtual power plant considering electricity trading," Applied Energy, Elsevier, vol. 351(C).
    18. Feng, Bin & Liu, Zhuping & Huang, Gang & Guo, Chuangxin, 2023. "Robust federated deep reinforcement learning for optimal control in multiple virtual power plants with electric vehicles," Applied Energy, Elsevier, vol. 349(C).
    19. Xie, Haonan & Ahmad, Tanveer & Zhang, Dongdong & Goh, Hui Hwang & Wu, Thomas, 2024. "Community-based virtual power plants’ technology and circular economy models in the energy sector: A Techno-economy study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    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. Li, Dongqing & Ren, Lina & Liu, Fucai & Gao, Juanjuan & Ma, Kai, 2025. "Two-time scale microgrid scheduling based on power fluctuation mitigation priority and model predictive control," Energy, Elsevier, vol. 324(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. Li, Yiran & Chang, Weiguang & Yang, Qiang, 2025. "Deep reinforcement learning based hierarchical energy management for virtual power plant with aggregated multiple heterogeneous microgrids," Applied Energy, Elsevier, vol. 382(C).
    2. Zhang, Mingze & Li, Weidong & Yu, Samson Shenglong & Wang, Haixia & Ba, Yu, 2024. "Optimal day-ahead large-scale battery dispatch model for multi-regulation participation considering full timescale uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    3. Shui, Jijun & Peng, Daogang & Zeng, Hui & Song, Yankan & Yu, Zhitong & Yuan, Xinran & Shen, Chen, 2024. "Optimal scheduling of multiple entities in virtual power plant based on the master-slave game," Applied Energy, Elsevier, vol. 376(PB).
    4. Wu, Haochi & Qiu, Dawei & Zhang, Liyu & Sun, Mingyang, 2024. "Adaptive multi-agent reinforcement learning for flexible resource management in a virtual power plant with dynamic participating multi-energy buildings," Applied Energy, Elsevier, vol. 374(C).
    5. Khalili, Siavash & Lopez, Gabriel & Breyer, Christian, 2025. "Role and trends of flexibility options in 100% renewable energy system analyses towards the Power-to-X Economy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 212(C).
    6. Yan, Xingyu & Gao, Ciwei & Francois, Bruno, 2025. "Multi-objective optimization of a virtual power plant with mobile energy storage for a multi-stakeholders energy community," Applied Energy, Elsevier, vol. 386(C).
    7. Guo, Litao & Li, Weidong & Zhang, Mingze, 2024. "Optimal capacity configuration and operation strategy of typical industry load with energy storage in fast frequency regulation," Energy, Elsevier, vol. 308(C).
    8. Durmaz, Tunç, 2016. "Precautionary Storage in Electricity Markets," Discussion Papers 2016/5, Norwegian School of Economics, Department of Business and Management Science.
    9. Sarhadi, Hassan & Naoum-Sawaya, Joe & Verma, Manish, 2020. "A robust optimization approach to locating and stockpiling marine oil-spill response facilities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    10. Lund, Henrik & Thellufsen, Jakob Zinck & Sorknæs, Peter & Mathiesen, Brian Vad & Chang, Miguel & Madsen, Poul Thøis & Kany, Mikkel Strunge & Skov, Iva Ridjan, 2022. "Smart energy Denmark. A consistent and detailed strategy for a fully decarbonized society," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    11. Göransson, Lisa & Goop, Joel & Unger, Thomas & Odenberger, Mikael & Johnsson, Filip, 2014. "Linkages between demand-side management and congestion in the European electricity transmission system," Energy, Elsevier, vol. 69(C), pages 860-872.
    12. Persson, Urban & Wiechers, Eva & Möller, Bernd & Werner, Sven, 2019. "Heat Roadmap Europe: Heat distribution costs," Energy, Elsevier, vol. 176(C), pages 604-622.
    13. Harasis, Salman & Khan, Irfan & Massoud, Ahmed, 2024. "Enabling large-scale integration of electric bus fleets in harsh environments: Possibilities, potentials, and challenges," Energy, Elsevier, vol. 300(C).
    14. Funcke, Simon & Bauknecht, Dierk, 2016. "Typology of centralised and decentralised visions for electricity infrastructure," Utilities Policy, Elsevier, vol. 40(C), pages 67-74.
    15. Serrano, Breno & Minner, Stefan & Schiffer, Maximilian & Vidal, Thibaut, 2024. "Bilevel optimization for feature selection in the data-driven newsvendor problem," European Journal of Operational Research, Elsevier, vol. 315(2), pages 703-714.
    16. David Drysdale & Brian Vad Mathiesen & Henrik Lund, 2019. "From Carbon Calculators to Energy System Analysis in Cities," Energies, MDPI, vol. 12(12), pages 1-21, June.
    17. Qiu, Ruozhen & Sun, Minghe & Lim, Yun Fong, 2017. "Optimizing (s, S) policies for multi-period inventory models with demand distribution uncertainty: Robust dynamic programing approaches," European Journal of Operational Research, Elsevier, vol. 261(3), pages 880-892.
    18. Li, Shuangqi & Zhao, Pengfei & Gu, Chenghong & Huo, Da & Zeng, Xianwu & Pei, Xiaoze & Cheng, Shuang & Li, Jianwei, 2022. "Online battery-protective vehicle to grid behavior management," Energy, Elsevier, vol. 243(C).
    19. Moreno, Blanca & López, Ana J. & García-Álvarez, María Teresa, 2012. "The electricity prices in the European Union. The role of renewable energies and regulatory electric market reforms," Energy, Elsevier, vol. 48(1), pages 307-313.
    20. Li, Ruonan & Mahalec, Vladimir, 2022. "Integrated design and operation of energy systems for residential buildings, commercial buildings, and light industries," Applied Energy, Elsevier, vol. 305(C).

    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:eee:energy:v:318:y:2025:i:c:s0360544225004335. 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.