Performance modeling of sodium-sulfur (NaS) batteries following optimized charging and discharging patterns

The integration of renewable energy sources into the power grid necessitates efficient and reliable energy storage solutions. Sodium‑sulfur (NaS) batteries, with their high energy density and long cycle life, offer a promising option for large-scale storage applications. This study presents a comprehensive performance modeling framework for NaS batteries, combining linear programming-based optimization with a reduced-order thermal-electrochemical model to evaluate system behavior under realistic operating conditions. Two case studies are analyzed: a hybrid photovoltaic (PV) and battery system designed to meet 50% of a 10 GWh annual electricity demand at the lowest cost, and a stand-alone battery system to achieve the highest revenues for electricity market arbitrage. The results highlight the effectiveness of the proposed two-step modeling approach in optimizing system size and operation while ensuring thermal safety. The hybrid system requires 5.43 MW of PV capacity and 10.11 MWh of battery storage, achieving a round-trip efficiency of 87.84%. The stand-alone system, with the same system size demonstrated lower operational frequency and energy throughput, with slightly lower efficiency (85.26%) and similar cooling demand. Thermal analysis revealed that the optimized charging/discharging profiles necessitate enhanced cooling capacity beyond manufacturer specifications to maintain safe operating temperatures. The study underscores the limitations of linear optimization in capturing thermal constraints and suggests that future work should focus on integrated optimization frameworks that incorporate thermal dynamics. Additionally, refining the thermal management logic could further improve system efficiency and reliability. These findings contribute to the development of more robust and economically viable NaS battery systems for renewable energy integration. • The two-step model combines linear optimization with thermal performance analysis. • NaS battery operation optimized for hybrid PV and stand-alone arbitrage scenarios • The thermal sub-model ensures safe operation under realistic charging profiles. • Stand-alone battery shows 30% less cycles but higher relative heating demand. • Highlights limitations of linear optimization in thermal-constrained systems