IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v384y2025ics0306261925000960.html
   My bibliography  Save this article

Data-Driven interval robust optimization method of VPP Bidding strategy in spot market under multiple uncertainties

Author

Listed:
  • Ma, Ying
  • Li, Zhen
  • Liu, Ruyi
  • Liu, Bin
  • Yu, Samson S.
  • Liao, Xiaozhong
  • Shi, Peng

Abstract

The participation of Virtual Power Plants (VPPs) in the spot market enhances the flexibility of modern power systems as renewable energy penetration increases. However, multiple uncertainties on the market, load, and generation sides can significantly affect the bidding strategies and operational efficiency of VPPs. This paper employs interval numbers generated by a data-driven model to capture the uncertainty and correlation of electricity prices in the spot market. Additionally, uncertainty sets are utilized to represent the variability in the number of electric vehicles (EVs) and photovoltaic (PV) power generation. A two-stage interval robust optimization model considering arbitrage opportunity is established to optimize the bidding strategies of a VPP that includes gas turbines, energy storage, PV systems, and EVs. An improved column-and-constraint generation (C&CG) algorithm is developed to solve this model.

Suggested Citation

  • Ma, Ying & Li, Zhen & Liu, Ruyi & Liu, Bin & Yu, Samson S. & Liao, Xiaozhong & Shi, Peng, 2025. "Data-Driven interval robust optimization method of VPP Bidding strategy in spot market under multiple uncertainties," Applied Energy, Elsevier, vol. 384(C).
    • Handle: RePEc:eee:appene:v:384:y:2025:i:c:s0306261925000960
    DOI: 10.1016/j.apenergy.2025.125366
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261925000960
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2025.125366?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. Alabi, Tobi Michael & Lu, Lin & Yang, Zaiyue, 2022. "Data-driven optimal scheduling of multi-energy system virtual power plant (MEVPP) incorporating carbon capture system (CCS), electric vehicle flexibility, and clean energy marketer (CEM) strategy," Applied Energy, Elsevier, vol. 314(C).
    2. Ju, Liwei & Tan, Zhongfu & Yuan, Jinyun & Tan, Qingkun & Li, Huanhuan & Dong, Fugui, 2016. "A bi-level stochastic scheduling optimization model for a virtual power plant connected to a wind–photovoltaic–energy storage system considering the uncertainty and demand response," Applied Energy, Elsevier, vol. 171(C), pages 184-199.
    3. 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).
    4. Qiu, Haifeng & Gu, Wei & Liu, Pengxiang & Sun, Qirun & Wu, Zhi & Lu, Xi, 2022. "Application of two-stage robust optimization theory in power system scheduling under uncertainties: A review and perspective," Energy, Elsevier, vol. 251(C).
    5. Shaolun Xu & Donghan Feng & Zheng Yan & Liang Zhang & Naihu Li & Lei Jing & Jianhui Wang, 2013. "Ant-Based Swarm Algorithm for Charging Coordination of Electric Vehicles," International Journal of Distributed Sensor Networks, , vol. 9(5), pages 268942-2689, May.
    6. Kong, Xiangyu & Xiao, Jie & Liu, Dehong & Wu, Jianzhong & Wang, Chengshan & Shen, Yu, 2020. "Robust stochastic optimal dispatching method of multi-energy virtual power plant considering multiple uncertainties," Applied Energy, Elsevier, vol. 279(C).
    7. Nosratabadi, Seyyed Mostafa & Hooshmand, Rahmat-Allah & Gholipour, Eskandar, 2017. "A comprehensive review on microgrid and virtual power plant concepts employed for distributed energy resources scheduling in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 341-363.
    8. Wang, Zizhao & Wu, Feng & Li, Yang & Li, Jingyan & Liu, Ying & Liu, Wenge, 2023. "Day-ahead dispatch approach for cascaded hydropower-photovoltaic complementary system based on two-stage robust optimization," Energy, Elsevier, vol. 265(C).
    9. Ju, Liwei & Lv, ShuoShuo & Zhang, Zheyu & Li, Gen & Gan, Wei & Fang, Jiangpeng, 2024. "Data-driven two-stage robust optimization dispatching model and benefit allocation strategy for a novel virtual power plant considering carbon-green certificate equivalence conversion mechanism," Applied Energy, Elsevier, vol. 362(C).
    10. Thomas, Dimitrios & Deblecker, Olivier & Ioakimidis, Christos S., 2018. "Optimal operation of an energy management system for a grid-connected smart building considering photovoltaics’ uncertainty and stochastic electric vehicles’ driving schedule," Applied Energy, Elsevier, vol. 210(C), pages 1188-1206.
    11. Cui, Xueyuan & Liu, Shu & Ruan, Guangchun & Wang, Yi, 2024. "Data-driven aggregation of thermal dynamics within building virtual power plants," Applied Energy, Elsevier, vol. 353(PB).
    12. Liu, Yangyang & Jiang, Chuanwen & Shen, Jingshuang & Hu, Jiakai & Luo, Yifan, 2015. "Coordination of hydro units with wind power generation based on RAROC," Renewable Energy, Elsevier, vol. 80(C), pages 783-792.
    13. Yu, Songyuan & Fang, Fang & Liu, Yajuan & Liu, Jizhen, 2019. "Uncertainties of virtual power plant: Problems and countermeasures," Applied Energy, Elsevier, vol. 239(C), pages 454-470.
    14. Ju, Liwei & Zhao, Rui & Tan, Qinliang & Lu, Yan & Tan, Qingkun & Wang, Wei, 2019. "A multi-objective robust scheduling model and solution algorithm for a novel virtual power plant connected with power-to-gas and gas storage tank considering uncertainty and demand response," Applied Energy, Elsevier, vol. 250(C), pages 1336-1355.
    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. Wang, Peng & Wu, Jiaqi & Ding, Yihong & Wang, Haili, 2025. "A time-series dynamic optimization model for distributed photovoltaic capacity planning considering the coupling of capacity and sales price," Renewable Energy, Elsevier, vol. 246(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. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N., 2022. "Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    2. Ju, Liwei & Yin, Zhe & Zhou, Qingqing & Li, Qiaochu & Wang, Peng & Tian, Wenxu & Li, Peng & Tan, Zhongfu, 2022. "Nearly-zero carbon optimal operation model and benefit allocation strategy for a novel virtual power plant using carbon capture, power-to-gas, and waste incineration power in rural areas," Applied Energy, Elsevier, vol. 310(C).
    3. Naval, Natalia & Yusta, Jose M., 2021. "Virtual power plant models and electricity markets - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    4. Mohammad Mohammadi Roozbehani & Ehsan Heydarian-Forushani & Saeed Hasanzadeh & Seifeddine Ben Elghali, 2022. "Virtual Power Plant Operational Strategies: Models, Markets, Optimization, Challenges, and Opportunities," Sustainability, MDPI, vol. 14(19), pages 1-23, September.
    5. Yang, Shenbo & Fang, Jiangpeng & Zhang, Zheyu & Lv, ShuoShuo & Lin, Hongyu & Ju, Liwei, 2024. "Two-stage coordinated optimal dispatching model and benefit allocation strategy for rural new energy microgrid," Energy, Elsevier, vol. 292(C).
    6. Amit Kumer Podder & Sayemul Islam & Nallapaneni Manoj Kumar & Aneesh A. Chand & Pulivarthi Nageswara Rao & Kushal A. Prasad & T. Logeswaran & Kabir A. Mamun, 2020. "Systematic Categorization of Optimization Strategies for Virtual Power Plants," Energies, MDPI, vol. 13(23), pages 1-46, November.
    7. Li, Qiang & Zhou, Yongcheng & Wei, Fanchao & Li, Shuangxiu & Wang, Zhonghao & Li, Jiajia & Zhou, Guowen & Liu, Jinfu & Yan, Peigang & Yu, Daren, 2024. "Multi-time scale scheduling for virtual power plants: Integrating the flexibility of power generation and multi-user loads while considering the capacity degradation of energy storage systems," Applied Energy, Elsevier, vol. 362(C).
    8. Wang, Jin & Zhao, Zhipeng & Zhou, Jinglin & Cheng, Chuntian & Su, Huaying, 2024. "Co-optimization for day-ahead scheduling and flexibility response mode of a hydro–wind–solar hybrid system considering forecast uncertainty of variable renewable energy," Energy, Elsevier, vol. 311(C).
    9. Shi, Yunhong & Li, Chengjiang & Wang, Honglei & Wang, Xiaolin & Negnevitsky, Michael, 2025. "A novel scheduling strategy of a hybrid wind-solar-hydro system for smoothing energy and power fluctuations," Energy, Elsevier, vol. 320(C).
    10. Tomasz Sikorski & Michal Jasiński & Edyta Ropuszyńska-Surma & Magdalena Węglarz & Dominika Kaczorowska & Paweł Kostyla & Zbigniew Leonowicz & Robert Lis & Jacek Rezmer & Wilhelm Rojewski & Marian Sobi, 2020. "A Case Study on Distributed Energy Resources and Energy-Storage Systems in a Virtual Power Plant Concept: Technical Aspects," Energies, MDPI, vol. 13(12), pages 1-30, June.
    11. 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).
    12. 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).
    13. Zhou, Yixing & Hou, Hongjuan & Yan, Haoran & Wang, Xi & Zhou, Rhonin, 2025. "Data-driven distributionally robust stochastic optimal dispatching method of integrated energy system considering multiple uncertainties," Energy, Elsevier, vol. 325(C).
    14. Fang, Fang & Yu, Songyuan & Liu, Mingxi, 2020. "An improved Shapley value-based profit allocation method for CHP-VPP," Energy, Elsevier, vol. 213(C).
    15. Tan, Mao & Li, Zibin & Su, Yongxin & Ren, Yuling & Wang, Ling & Wang, Rui, 2024. "Dual time-scale robust optimization for energy management of distributed energy community considering source-load uncertainty," Renewable Energy, Elsevier, vol. 226(C).
    16. Tong Xing & Hongyu Lin & Zhongfu Tan & Liwei Ju, 2019. "Coordinated Energy Management for Micro Energy Systems Considering Carbon Emissions Using Multi-Objective Optimization," Energies, MDPI, vol. 12(23), pages 1-27, November.
    17. Tan, Caixia & Wang, Jing & Geng, Shiping & Pu, Lei & Tan, Zhongfu, 2021. "Three-level market optimization model of virtual power plant with carbon capture equipment considering copula–CVaR theory," Energy, Elsevier, vol. 237(C).
    18. González-Garrido, A. & Gaztañaga, H. & Saez-de-Ibarra, A. & Milo, A. & Eguia, P., 2020. "Electricity and reserve market bidding strategy including sizing evaluation and a novel renewable complementarity-based centralized control for storage lifetime enhancement," Applied Energy, Elsevier, vol. 262(C).
    19. Kong, Xiangyu & Xiao, Jie & Wang, Chengshan & Cui, Kai & Jin, Qiang & Kong, Deqian, 2019. "Bi-level multi-time scale scheduling method based on bidding for multi-operator virtual power plant," Applied Energy, Elsevier, vol. 249(C), pages 178-189.
    20. Kim, Seokwoo & Choi, Dong Gu, 2024. "A sample robust optimal bidding model for a virtual power plant," European Journal of Operational Research, Elsevier, vol. 316(3), pages 1101-1113.

    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:384:y:2025:i:c:s0306261925000960. 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.