A flexible model for economic operational management of grid battery energy storage

To connect energy storage operational planning with real-time battery control, this paper integrates a dynamic battery model with an optimization program. First, we transform a behavioral circuit model designed to describe a variety of battery chemistries into a set of coupled nonlinear differential equations. Then, we discretize the differential equations to integrate the battery model with a GAMS (General Algebraic Modeling System) optimization program, which decides when the battery should charge and discharge to maximize its operating revenue. We demonstrate the capabilities of our model by applying it to lithium-ion (Li-ion) energy storage operating in Texas' restructured electricity market. By simulating 11 years of operation, we find that our model can robustly compute an optimal charge-discharge schedule that maximizes daily operating revenue without violating a battery's operating constraints. Furthermore, our results show there is significant variation in potential operating revenue from one day to the next. The revenue potential of Li-ion storage varies from approximately $0–1800/MWh of energy discharged, depending on the volatility of wholesale electricity prices during an operating day. Thus, it is important to consider the material degradation-related “cost” of performing a charge-discharge cycle in battery operational management, so that the battery only operates when revenue exceeds cost.