IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v376y2024ipas0306261924015253.html

Optimal aggregation and disaggregation for coordinated operation of virtual power plant with distribution network operator

Author

Listed:
  • Liu, Xin
  • Lin, Xueshan
  • Qiu, Haifeng
  • Li, Yang
  • Huang, Tao

Abstract

Virtual power plants (VPPs) offer an effective approach for managing distributed energy resources (DERs), including microturbines, distributed generators, demand response aggregators, and energy storage systems. This technology significantly enhances the economic efficiency and flexibility of distribution network systems. This study aims to facilitate a flexible power exchange between the distribution network system and the upper-level grid by aggregating the power flexibility of heterogeneous DERs via a VPP. Additionally, it introduces a methodology for optimal aggregation and disaggregation within a coordinated operation framework between the VPP and distribution network operator (DNO). On one hand, the VPP can determine its day-ahead feasible region and real-time flexible regulation power based on operational constraints of DERs and representative data provided by the DNO, circumventing the need for detailed network information. On the other hand, day-ahead and real-time correction procedures for the DER cost functions are proposed, effectively neutralizing the impact of network operational constraints on these cost functions. Consequently, precise cost functions for both the active power and the flexible regulation power aggregated by the VPP are derived. Employing this aggregated cost function enables the determination of a cost-minimized optimal scheduling solution in real-time by solving a fundamental economic dispatch problem, significantly alleviating computational demands. Finally, case studies demonstrate that the proposed method achieves an error in aggregated power of only 0.77%, compared to the precise computation method that requires comprehensive system information. The proposed optimal VPP disaggregation scheme exhibits power discrepancies of 0.63% and cost discrepancies of 0.91% relative to the precise method. Additionally, when implementing the most cost-effective demand response plan based on the proposed cost function, the average costs for aggregators are reduced by 19.7%.

Suggested Citation

  • Liu, Xin & Lin, Xueshan & Qiu, Haifeng & Li, Yang & Huang, Tao, 2024. "Optimal aggregation and disaggregation for coordinated operation of virtual power plant with distribution network operator," Applied Energy, Elsevier, vol. 376(PA).
    • Handle: RePEc:eee:appene:v:376:y:2024:i:pa:s0306261924015253
    DOI: 10.1016/j.apenergy.2024.124142
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261924015253
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2024.124142?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, XiaoWei & Yu, Xiaoping & Ye, Xinping & Pirouzi, Sasan, 2023. "Economic energy managementof networked flexi-renewable energy hubs according to uncertainty modeling by the unscented transformation method," Energy, Elsevier, vol. 278(PB).
    2. Liang, Hejun & Pirouzi, Sasan, 2024. "Energy management system based on economic Flexi-reliable operation for the smart distribution network including integrated energy system of hydrogen storage and renewable sources," Energy, Elsevier, vol. 293(C).
    3. Chen, Lin & Tang, Zhiyuan & He, Shuaijia & Liu, Junyong, 2024. "Feasible operation region estimation of virtual power plant considering heterogeneity and uncertainty of distributed energy resources," Applied Energy, Elsevier, vol. 362(C).
    4. Liu, Xin & Huang, Tao & Qiu, Haifeng & Li, Yang & Lin, Xueshan & Shi, Jianxiong, 2024. "Optimal aggregation of a virtual power plant based on a distribution-level market with the participation of bounded rational agents," Applied Energy, Elsevier, vol. 364(C).
    5. Oshnoei, Arman & Kheradmandi, Morteza & Blaabjerg, Frede & Hatziargyriou, Nikos D. & Muyeen, S.M. & Anvari-Moghaddam, Amjad, 2022. "Coordinated control scheme for provision of frequency regulation service by virtual power plants," Applied Energy, Elsevier, vol. 325(C).
    6. Abdulaal, Ahmed & Moghaddass, Ramin & Asfour, Shihab, 2017. "Two-stage discrete-continuous multi-objective load optimization: An industrial consumer utility approach to demand response," Applied Energy, Elsevier, vol. 206(C), pages 206-221.
    7. Ding, Zhetong & Li, Yaping & Zhang, Kaifeng & Peng, Jimmy Chih-Hsien, 2024. "Two-stage dynamic aggregation involving flexible resource composition and coordination based on submodular optimization," Applied Energy, Elsevier, vol. 360(C).
    8. Zhang, Tianhan & Qiu, Weiqiang & Zhang, Zhi & Lin, Zhenzhi & Ding, Yi & Wang, Yiting & Wang, Lianfang & Yang, Li, 2023. "Optimal bidding strategy and profit allocation method for shared energy storage-assisted VPP in joint energy and regulation markets," Applied Energy, Elsevier, vol. 329(C).
    9. Dong, Lianxin & Fan, Shuai & Wang, Zhihua & Xiao, Jucheng & Zhou, Huan & Li, Zuyi & He, Guangyu, 2021. "An adaptive decentralized economic dispatch method for virtual power plant," Applied Energy, Elsevier, vol. 300(C).
    10. Liu, Xin & Li, Yang & Wang, Li & Tang, Junbo & Qiu, Haifeng & Berizzi, Alberto & Valentin, Ilea & Gao, Ciwei, 2024. "Dynamic aggregation strategy for a virtual power plant to improve flexible regulation ability," Energy, Elsevier, vol. 297(C).
    11. Esfahani, Moein & Alizadeh, Ali & Amjady, Nima & Kamwa, Innocent, 2024. "A distributed VPP-integrated co-optimization framework for energy scheduling, frequency regulation, and voltage support using data-driven distributionally robust optimization with Wasserstein metric," Applied Energy, Elsevier, vol. 361(C).
    12. Gao, Hongchao & Jin, Tai & Feng, Cheng & Li, Chuyi & Chen, Qixin & Kang, Chongqing, 2024. "Review of virtual power plant operations: Resource coordination and multidimensional interaction," Applied Energy, Elsevier, vol. 357(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. Esfahani, Moein & Alizadeh, Ali & Cao, Bo & Kamwa, Innocent & Xu, Minghui, 2025. "Bridging theory and practice: A comprehensive review of virtual power plant technologies and their real-world applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 222(C).
    2. Yang, Shaohua & Lao, Keng-Weng & Hui, Hongxun & Su, Jinshuo & Wang, Sheng, 2025. "Secure frequency regulation in power system: A comprehensive defense strategy against FDI, DoS, and latency cyber-attacks," Applied Energy, Elsevier, vol. 379(C).
    3. Zhikai Zhang & Yanfang Wei, 2025. "Dispatch Instruction Disaggregation for Virtual Power Plants Using Multi-Parametric Programming," Energies, MDPI, vol. 18(15), pages 1-20, July.
    4. Li Guo & Guiyuan Xue & Zheng Xu & Huixiang Li & Jiacheng Li & Xun Dou, 2025. "Multi-Objective Time-Domain Coupled Feasible Region Construction Method for Virtual Power Plant Considering Global Stability," Energies, MDPI, vol. 18(11), pages 1-19, June.

    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. Kaiss, Mateus & Wan, Yihao & Gebbran, Daniel & Vila, Clodomiro Unsihuay & Dragičević, Tomislav, 2025. "Review on Virtual Power Plants/Virtual Aggregators: Concepts, applications, prospects and operation strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 211(C).
    2. Yang, Yilong & Fan, Shuai & Xiao, Jucheng & Huang, Renke & He, Guangyu, 2025. "Aggregation and packaging of distributed energy resources: A time-coupled flexibility-demand-oriented method," Energy, Elsevier, vol. 334(C).
    3. 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).
    4. Du, Haoming & Hu, Junjie & Fang, Yuxuan & Xie, Dongliang, 2025. "Optimal bidding strategy for virtual power plant participating in joint energy and reserve market considering physical-economic feasible operation region," Energy, Elsevier, vol. 336(C).
    5. Tan, Mao & Jiang, Hongwei & Kuang, Yi & Li, Kang & Wang, Rui & Li, Zibin, 2025. "Electricity–carbon dual response for energy-intensive enterprise: A co-optimization approach," Renewable Energy, Elsevier, vol. 251(C).
    6. Hao, Junhong & Feng, Xiaolong & Chen, Xiangru & Jin, Xilin & Wang, Xingce & Hao, Tong & Hong, Feng & Du, Xiaoze, 2024. "Optimal scheduling of active distribution network considering symmetric heat and power source-load spatial-temporal characteristics," Applied Energy, Elsevier, vol. 373(C).
    7. Liu, Yuanchao & Zheng, Ruifan & Shen, Rendong & Zhao, Jun & Shi, Zekun & Wang, Guangliang & Yang, Dongfang & Li, Yang, 2025. "Research on capacity configuration optimization of integrated energy system by integrating energy hub and response surface methodology," Energy, Elsevier, vol. 330(C).
    8. Ren, Junzhi & Zeng, Yuan & Qin, Chao & Li, Bao & Wang, Ziqiang & Yuan, Quan & Zhai, Hefeng & Li, Peng, 2024. "Characterization and application of flexible operation region of virtual power plant," Applied Energy, Elsevier, vol. 371(C).
    9. G., Varathan & J., Belwin Edward, 2024. "A review of uncertainty management approaches for active distribution system planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 205(C).
    10. Xu, Yijun & Zhang, Xuan & Li, Ji, 2024. "Multiple energy planning in the energy hub considering renewable sources, electric vehicles and management in the daily electricity market with wind multi-objective optimization algorithm," Energy, Elsevier, vol. 309(C).
    11. Noorollahi, Younes & Zahedi, Rahim & Ahmadi, Esmaeil & Khaledi, Arian, 2025. "Low carbon solar-based sustainable energy system planning for residential buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 207(C).
    12. Lei, Xiang & Yu, Hang & Zhong, Jiahao & Shao, Ziyun & Jian, Linni, 2025. "A data-driven robust optimal day-ahead bidding strategy considering V2G operation for distribution-system-side virtual power plant," Energy, Elsevier, vol. 338(C).
    13. Koltsaklis, Nikolaos E. & Knápek, Jaroslav, 2025. "Integrated market scheduling with flexibility options," Renewable and Sustainable Energy Reviews, Elsevier, vol. 208(C).
    14. Fei Liu & Shaokang Qi & Shibin Wang & Xu Tian & Liantao Liu & Xue Zhao, 2025. "Robust Trading Decision-Making Model for Demand-Side Resource Aggregators Considering Multi-Objective Cluster Aggregation Optimization," Energies, MDPI, vol. 18(2), pages 1-24, January.
    15. Wang, Qihui & Li, Zhengshuo, 2026. "Learning-to-optimize infused decentralized disaggregation for multi-entity technical VPP considering equity and privacy," Applied Energy, Elsevier, vol. 405(C).
    16. Lin, Chengrong & Hu, Bo & Tai, Heng-Ming & Shao, Changzheng & Xie, Kaigui & Wang, Yu, 2024. "Performance optimization of VPP in fast frequency control ancillary service provision," Applied Energy, Elsevier, vol. 376(PB).
    17. Weigang Jin & Peihua Wang & Jiaxin Yuan, 2024. "Key Role and Optimization Dispatch Research of Technical Virtual Power Plants in the New Energy Era," Energies, MDPI, vol. 17(22), pages 1-24, November.
    18. Guo, Xinman & Cao, Sunliang, 2025. "The techno-economic analysis of hybrid coastal and offshore ocean energy system for the smart charging of cross-harbour zero-emission ferries and electric vehicles," Applied Energy, Elsevier, vol. 402(PA).
    19. Fan, Yukun & Liu, Weifeng & Zhu, Feilin & Wang, Sen & Yue, Hao & Zeng, Yurou & Xu, Bin & Zhong, Ping-an, 2024. "Short-term stochastic multi-objective optimization scheduling of wind-solar-hydro hybrid system considering source-load uncertainties," Applied Energy, Elsevier, vol. 372(C).
    20. Fu, Yang & Shan, Jie & Li, Zhenkun & Xie, BoLin & Pan, Jeng-Shyang, 2025. "The optimal bidding strategy for multi-energy prosumers in the double auction electricity-heat market: A bidding space model," Energy, Elsevier, vol. 314(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:appene:v:376:y:2024:i:pa:s0306261924015253. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.