Iterative sizing methodology for photovoltaic plants coupled with battery energy storage systems to ensure smooth power output and power availability

• A methodology for sizing a PV–BESS in PV smoothing applications was introduced. • The methodology was applied to a case study, and the optimum size was determined. • The methodology includes validated PV data, a model for PV–BESS dynamics, and cost. • The LFP–based BESS is more cost–effective than an NMC–based BESS. Photovoltaic (PV) solar energy is a fundamental technology that will help transition from a fossil fuel–based energy mix to a future with high shares of renewable energy. To do so, PV plants coupled with energy storage systems can accumulate excess power and dispatch it when PV generation changes, performing PV smoothing. While coupling PV plants with battery energy storage systems (BESS) offers a solution, current methodologies often need to thoroughly describe the interplay between BESS energy capacity, power rating, and the long–term impacts of battery degradation. This paper addresses this gap by proposing a four–step methodology that optimizes BESS sizing for PV plants, accounting for both cycling and calendar aging effects on system performance and the economic implications of battery replacements. We use a model that considers the degradation of PV modules and two Li–ion battery types (LiFePO 4 , LFP, and LiNiMnCoO 2 , NMC). A 16.3 MW PV plant is simulated along with the BESS to test the methodology. The results indicate that an LFP–based BESS of 2.5 MWh with a rated power of 1.25 MW ensures a stable output power with variation below 10% of the rated PV plant 98 % of the time. In contrast, an NMC–based BESS, while effective in reducing non–compliance, incurs higher costs due to more frequent battery replacements, making it less economically viable. The methodology and results presented in this paper provide valuable insights for designing cost–effective and reliable energy storage solutions in PV plants, ensuring compliance with set power availability.