Joint sizing and energy management optimization with dynamic battery lifetime modeling in residential PV–battery systems

Battery Energy Storage Systems (BESS) are a critical component in residential PV–battery systems due to their high cost and lifetime variability caused by aging. This paper presents a joint optimization framework for system sizing and operation that integrates a dynamic lifetime model combining calendar and cyclic degradation mechanisms. The proposed approach links degradation behavior with both operational and economic decisions through annualized cost formulations. A residential case study in Tallinn is conducted under self-consumption and grid-selling scenarios. Results show that optimized operation extends battery lifetime beyond 13 years and reduces the payback period from 16 to 7 years in the grid-selling case. Seasonal analyses indicate that degradation is dominated by cyclic aging, with annual capacity fade (i.e., SoH loss) between 1.3% and 1.7%. The impact of solar irradiance uncertainty was also evaluated, showing cost deviations below 8% and a lifetime reduction of about 1.5 years.