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Multi-market revenue optimization for integrated wind and hybrid energy storage systems

Author

Listed:
  • Aghamohammadloo, Hossein
  • Mohammadi-Ivatloo, Behnam
  • Safdarian, Amir
  • Tikka, Ville
  • Aghaei, Jamshid
  • Pinto Mendes, Gonçalo

Abstract

This study presents a comprehensive revenue stacking optimization framework that integrates wind power with hybrid energy storage systems (HESS) for coordinated participation in multiple electricity markets. The framework features a hybrid configuration of battery energy storage (BES) and supercapacitors (SC), designed to exploit their complementary strengths, SC for ultra-fast frequency support and BES for sustained energy delivery. A comprehensive co-optimization approach is formulated to simultaneously capture the capacity and energy revenue streams from the day-ahead (DA) electricity market and ancillary services, including frequency regulation and balancing market. The model explicitly incorporates battery degradation costs, market bidding rules, and recent regulatory changes, ensuring alignment with evolving electricity market structures. A Mixed-Integer Linear Programming (MILP) approach is used to assess the economic value of multi-market participation under realistic system and market constraints. The proposed framework is applied to the electricity market in Finland, demonstrating the significant revenue improvement and financial viability enabled by coordinated multi-market engagement. The study also highlights the critical role of activation-aware modeling in capturing the uncertainties of frequency services and ensuring long-term system reliability and profitability.

Suggested Citation

  • Aghamohammadloo, Hossein & Mohammadi-Ivatloo, Behnam & Safdarian, Amir & Tikka, Ville & Aghaei, Jamshid & Pinto Mendes, Gonçalo, 2026. "Multi-market revenue optimization for integrated wind and hybrid energy storage systems," Applied Energy, Elsevier, vol. 402(PB).
  • Handle: RePEc:eee:appene:v:402:y:2026:i:pb:s030626192501503x
    DOI: 10.1016/j.apenergy.2025.126773
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