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

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  • 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
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