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Main Authors: Hu, Ruimeng, Ludkovski, Mike, Zhang, Hezhong
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2605.01178
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author Hu, Ruimeng
Ludkovski, Mike
Zhang, Hezhong
author_facet Hu, Ruimeng
Ludkovski, Mike
Zhang, Hezhong
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2605_01178
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Modeling Stochastic Multi-Agent Interaction in Intraday Battery Energy Storage Dispatch with Market Power
Hu, Ruimeng
Ludkovski, Mike
Zhang, Hezhong
Optimization and Control
Mathematical Finance
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.
title Modeling Stochastic Multi-Agent Interaction in Intraday Battery Energy Storage Dispatch with Market Power
topic Optimization and Control
Mathematical Finance
url https://arxiv.org/abs/2605.01178