Optimal utilization strategy of the LiFePO4 battery storage

The paper provides a comprehensive battery storage modeling approach, which accounts for operation-and degradation-aware characteristics and can be used in optimization problem formulations. Particularly, Mixed Integer Linear Programming (MILP) compatible models have been developed for the lithium iron phosphate (LiFePO4) battery storage using the Special Order Sets 2 to represent the nonlinear characteristics, including efficiency, internal resistance growth, and capacity fade. Such formulation can be used in problems related to various applications, i.e., power systems, smart grid, and vehicular applications, and it allows finding the globally optimal solution using off-the-shelf academic and commercial solvers. In the numerical study, the proposed modeling approach has been applied to realistic scenarios of peak-shaving, where the importance of considering the developed models is explicitly demonstrated. Operation-and degradation-aware technoeconomic analysis showed that the optimal battery capacity is driven by operating rather than service requirements. Particularly, a considerable battery over-sizing becomes economically feasible when the battery storage is used more extensively. Another finding suggests that to achieve the maximum value from battery storage, its operation strategy needs to be significantly modified during the course of its lifetime. In the scenarios considered, the charging time gradually increased from four to seven hours, while the average SoC decreased by 20%. Such an adaptable scheduling results in reduced battery degradation and a longer lifetime, which may provide as much as 12.1% of savings in the battery storage system project.

Automated summary

The paper proposes a comprehensive battery storage modeling approach and applies it to realistic scenarios of peak-shaving, demonstrating the importance of considering the developed models. The study finds that larger battery capacity becomes economically feasible when the battery is used more extensively. Additionally, adapting the operation strategy during the battery's lifetime reduces degradation and extends its lifespan, resulting in potential cost savings of up to 12.1% in the battery storage system project.