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

TL;DR

This paper presents a stochastic game-theoretic model for intraday battery energy storage dispatch, analyzing market power, externalities, and the impact of decentralized BESS deployment on electricity prices.

Contribution

It introduces a semi-explicit equilibrium framework for multi-agent BESS dispatch considering market power and heterogeneity, with analysis of large-agent asymptotics.

Findings

Equilibrium controls and prices characterized via Riccati equations.

Market power effects and externalities quantified.

Large-agent limit behavior analyzed.

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.