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Multi-market value-stacking: Battery control for combined imbalance participation and non-uniform FCR bidding
Celle Hendri · 2026-05-26 · via cs.AI updates on arXiv.org

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Abstract:The growing share of Renewable Energy Sources (RES) in modern power systems increases both grid imbalances and frequency deviations, reinforcing the need for ancillary services such as Frequency Containment Reserve (FCR) and passive balancing. Battery Energy Storage Systems (BESS) are well-suited for these services, but prior research typically relies on uniform FCR bids that remain constant throughout the control period. Such static bids fail to fully exploit BESS flexibility, as they do not balance the trade-off between reserving energy for FCR delivery and using it for imbalance arbitrage, limiting the achievable value in value-stacking settings. To address this limitation, we propose a two-stage control framework for the European context that introduces non-uniform FCR bids. In the first stage, we derive a time-varying bid sequence using data-driven Monte Carlo (MC) optimization. In the second stage, a Deep Reinforcement Learning (DRL) agent leverages the residual flexibility for real-time imbalance trading while proactively managing the State of Energy (SoE) to ensure compliance with FCR requirements. The framework is presented as a proof of concept, highlighting the potential benefits of time-varying bidding strategies. By incorporating daily cycle budgets and time-varying reserve commitments, our approach achieves a 7.56% profit increase compared to uniform baselines. These results show that non-uniform bidding can unlock additional value by more effectively aligning reserve obligations with rapidly changing imbalance opportunities.
Comments: 5 pages, 2 figures. Presented at ACM Sustainability Week 2026 (ACM Sustainability Week Companion 26), June 22-25, 2026, Banff, AB, Canada
Subjects: Systems and Control (eess.SY); Artificial Intelligence (cs.AI)
ACM classes: C.4; I.2.6; G.1.6; J.7
Cite as: arXiv:2605.23964 [eess.SY]
  (or arXiv:2605.23964v1 [eess.SY] for this version)
  https://doi.org/10.48550/arXiv.2605.23964

arXiv-issued DOI via DataCite

Related DOI: https://doi.org/10.1145/3765611.3815430

DOI(s) linking to related resources

Submission history

From: Celle Hendrickx [view email]
[v1] Tue, 12 May 2026 17:32:11 UTC (55 KB)