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Modeling Stochastic Multi-Agent Interaction in Intraday Battery Energy Storage Dispatch with Market Power

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  • Ruimeng Hu
  • Mike Ludkovski
  • Hezhong Zhang

Abstract

We develop a stochastic game-theoretic model for intraday dispatch of grid-scale battery energy storage systems (BESSs). We assume that each BESS operator competitively manages her state-of-charge to maximize energy arbitrage revenues, driven by the endogenized electricity price that depends on the sum of the charging rates. We characterize the Nash equilibrium of the resulting finite-player linear-quadratic differential game with a shared stochastic driver, obtaining semi-explicit representations of equilibrium feedback controls and equilibrium prices both in the general heterogeneous and the simplified homogeneous BESS setting, via a system of Riccati equations. We then analyze competitive effects, including the marginal externality of additional BESS entering the market, the benefit of coordination and the corresponding market power of large operators, and supply effects from hybrid-type BESSs. We further study the asymptotic regime as the number of agents grows large. Our model provides a quantitative testbed to study the impact of decentralized BESS deployment on the grid and the resulting reduction in daily price spreads.

Suggested Citation

  • Ruimeng Hu & Mike Ludkovski & Hezhong Zhang, 2026. "Modeling Stochastic Multi-Agent Interaction in Intraday Battery Energy Storage Dispatch with Market Power," Papers 2605.01178, arXiv.org.
    • Handle: RePEc:arx:papers:2605.01178
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    References listed on IDEAS

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    4. Olivier F'eron & Peter Tankov & Laura Tinsi, 2020. "Price formation and optimal trading in intraday electricity markets with a major player," Papers 2011.07655, arXiv.org.
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    7. Emmanuel Gobet & Maxime Grangereau, 2026. "Federated Stochastic Control of Numerous Heterogeneous Energy Storage Systems," Journal of Optimization Theory and Applications, Springer, vol. 208(3), pages 1-34, March.
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