IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i2p284-d1564301.html
   My bibliography  Save this article

Coordinated Optimization of Multi-Regional Integrated Energy Service Providers with Flexible Reserve Resources

Author

Listed:
  • Xueting Wang

    (Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station, China Three Gorges University, Yichang 443002, China
    College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443002, China)

  • Hao Zhong

    (Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station, China Three Gorges University, Yichang 443002, China
    College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443002, China)

  • Xianqiu Zou

    (State Grid Hunan Electric Power Co., Ltd. Loudi Power Supply Company, Loudi 417000, China)

  • Qiujie Wang

    (Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station, China Three Gorges University, Yichang 443002, China
    College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443002, China)

  • Lanfang Li

    (Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station, China Three Gorges University, Yichang 443002, China
    College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443002, China)

Abstract

Aiming at solving the problem of new energy and load uncertainty leading to a steep increase in the demand for flexible reserve resources by integrated energy service providers (IESPs), a coordinated and optimized scheduling method for multi-region integrated energy service providers considering flexible reserve resources is proposed. First, for the uncertainty of new energy and load, Latin hypercube sampling is used to generate scenarios, and the scenarios are reduced by a K-means clustering algorithm. Second, based on the interaction relationship between the active distribution network (ADN) and multi-region IESPs, a mixed game model of the ADN and IESP alliance is established. ADN guides IESPs to optimize their operation by setting prices for electricity and reserves, and IESPs fully tap their own flexible reserve resources according to the prices set by ADN and achieve power interoperability through the interaction of IESPs in multiple regions to synergistically cope with the uncertainties of new energy and load. Finally, the example results show that the model proposed in this paper is able to realize the allocation of flexibility resources in a wider range, reduce the reserve pressure on the superior grid, and improve the profitability of IESPs.

Suggested Citation

  • Xueting Wang & Hao Zhong & Xianqiu Zou & Qiujie Wang & Lanfang Li, 2025. "Coordinated Optimization of Multi-Regional Integrated Energy Service Providers with Flexible Reserve Resources," Energies, MDPI, vol. 18(2), pages 1-19, January.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:2:p:284-:d:1564301
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/2/284/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/18/2/284/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lu, Qing & Guo, Qisheng & Zeng, Wei, 2022. "Optimization scheduling of integrated energy service system in community: A bi-layer optimization model considering multi-energy demand response and user satisfaction," Energy, Elsevier, vol. 252(C).
    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. Wang, Tonghe & Hua, Haochen & Shi, Tianying & Wang, Rui & Sun, Yizhong & Naidoo, Pathmanathan, 2024. "A bi-level dispatch optimization of multi-microgrid considering green electricity consumption willingness under renewable portfolio standard policy," Applied Energy, Elsevier, vol. 356(C).
    2. Gianluca Carraro & Enrico Dal Cin & Sergio Rech, 2024. "Integrating Energy Generation and Demand in the Design and Operation Optimization of Energy Communities," Energies, MDPI, vol. 17(24), pages 1-20, December.
    3. Jiang, Meihui & Xu, Zhenjiang & Zhu, Hongyu & Hwang Goh, Hui & Agustiono Kurniawan, Tonni & Liu, Tianhao & Zhang, Dongdong, 2024. "Integrated demand response modeling and optimization technologies supporting energy internet," Renewable and Sustainable Energy Reviews, Elsevier, vol. 203(C).
    4. Kalina, Jacek, 2023. "The quest for game changers - Review of new trends and innovations in the design of large-scale energy systems," Energy, Elsevier, vol. 277(C).
    5. Xiang, Leijun & Lin, Qichao & Zhu, Shanying & Gao, Minkun, 2024. "Extended matrix modeling of integrated energy systems considering network dynamic characteristics and source–load uncertainty," Energy, Elsevier, vol. 312(C).
    6. Yan, Haoran & Hou, Hongjuan & Deng, Min & Si, Lengge & Wang, Xi & Hu, Eric & Zhou, Rhonin, 2024. "Stackelberg game theory based model to guide users’ energy use behavior, with the consideration of flexible resources and consumer psychology, for an integrated energy system," Energy, Elsevier, vol. 288(C).
    7. Niño-Zambrano, Miguel-Angel & Cobos-Lozada, Carlos-Alberto & Mendoza-Becerra, Martha-Eliana & Ordóñez-Erazo, Hugo-Armando & García-Sierra, Rodolfo, 2024. "System dynamics model for analysis of demand response on incorporating autoswitch in the Colombian electrical sector," Energy Policy, Elsevier, vol. 193(C).

    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:2:p:284-:d:1564301. 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.