The fundamental value of information and strategy in stochastic management of distributed energy storage

Determining the value of distributed energy storage for grid operation and control requires modeling and simulation of optimal energy scheduling. This paper evaluates Stochastic Dynamic Programming (SDP) and Stochastic Game Theory (SGT) methods for scheduling energy usage in a system with storage, and quantitatively evaluates these scheduling methods for energy storage in commercial buildings. With varying probabilities of load, an optimal energy storage strategy is derived that provides a way to determine the value of load forecasting on a daily basis and evaluates this strategy in the face of energy use incentives. Theoretical results are matched with modeling and simulation.