Volatile electricity markets and battery storage: A model-based approach for optimal control

Abstract

Grid connected energy storage systems provide a strategic advantage by exploiting electricity market price fluctuations, thereby significantly reducing energy consumption costs. This paper presents a general framework for minimizing electricity consumption costs by formulating the problem as a stochastic optimal control problem for a stationary battery storage device (SBSD). We propose a realistic model for electricity spot prices calibrated with real data, alongside a detailed model of battery dynamics with practical parameters. The control problem is solved in a discrete time setting by combining dynamic programming with the least squares Monte Carlo method, allowing us to approximate the value function and the optimal policy under both state of charge and voltage constraints. Using the derived optimal policy, we estimate the lower bound of electricity consumption costs across multiple price trajectories. The results demonstrate that the SBSD can substantially reduce consumption costs, with savings increasing with battery duration. After one year, a battery with 12 hours duration achieves approximately 11% cost reduction, while 24 hours battery achieves 21%, compared to a scenario without storage. Finally, we estimate the amortization time (the period required for cumulative savings to offset the initial investment). After 6.7 years for the 12 hours battery and 9.9 years for the 24 hours battery, the amortization time is reached.