Modeling stationary lithium-ion batteries for optimization and predictive control

Abstract

Accurately modeling stationary battery storage behavior is crucial to pursuing cost-effective distributed energy resource opportunities. In this paper, a lithium-ion battery model was derived for building-integrated battery use cases. The proposed battery model aims to balance speed and accuracy when modeling battery behavior for real-time predictive control and optimization. To achieve these goals, a mixed modeling approach incorporates regression fits to experimental data and an equivalent circuit to model battery behavior. The proposed battery model is validated through comparison to manufacturer data. Additionally, a dynamic test case demonstrates the effects of using regression models to represent cycling losses and capacity fading. A proof-of-concept optimization test case with time-of-use pricing is performed to demonstrate how the battery model could be included in an optimization framework.