Battery Energy Storage Systems (BESS) are a key mechanism for decarbonizing the grid by complementing and time-shifting the inherent uncertainty of weather-contingent variable renewable energy assets. The rapid build out of BESS capacity is reshaping the power grid, adding a new class of energy resources with multiple flexibilities. This project will provide new tools for designing efficient market policies that maximize the benefits of BESS and fairly incentivize private BESS operators to provide valuable grid services, underpinning its stable daily operations. The resulting insights will support an efficient and sustainable grid that is resilient, secure and prevents predatory behavior. The project will develop new stochastic modeling frameworks for management of BESS, addressing short-term operation of a single BESS, BESS joint bidding for day-ahead and intra-day ancillary service provision and energy trading markets, and the aggregate behavior of competitive price-making BESS. Using the lens of stochastic games, the PIs will characterize mean-field and N-player equilibria for a market with many BESS acting as non-cooperative players. An integral part of this project is to construct and study numeric algorithms for intra-day BESS management that take into account the operating-scale uncertainty in grids with high renewable penetration. Research activities are grounded in scalable algorithmic development and will be tested on realistic-scale simulators, offering tech-t