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Batteries are integral to modern electrical grids, enhancing flexibility and supporting the integration of renewable energy. However, predicting the economic viability of these systems remains challenging due to the complex interplay between operational strategies and battery degradation. These dynamics are studied in the context of Eskilstuna’s electrical grid, with a focus on one selected transformer station. The analysis uses real-world data and advanced battery aging models from BatteryStateful, developed by the U.S. National Renewable Energy Laboratory (NREL). A novel and practical methodology is developed to identify the Discharge Penalty Cost (DPC) threshold that maximizes the long-term profitability by considering advanced degradation effects. This study shows how to determine the minimum profit required per cycle for the cycle to be economically justified, aiming to maximize the battery’s lifetime value. Employing a mixed-integer linear programming (MILP) approach introducing the DPC in the objective function, and in parallel running full life advanced aging simulations (optimization-simulation framework), the study explores the trade-offs between peak shaving, charge/discharge cycles, and battery lifespan. A minimum profit of 14,5 EUR/MW in this use case study ensures maximum discounted income, and should be used for generating the daily dispatch plan of the battery. The discussion highlights the crucial role of degradation cost estimation in dispatch optimization. These insights offer valuable guidance to utility companies seeking to optimize energy storage deployment, balancing economic objectives with battery life considerations in real-world scenarios.