## 5 Conclusions  
The study results reported in this paper demonstrate that fuzzy logic-enhanced power smoothing methods combined with LI-ION BESS are highly effective in mitigating PV power variability and improving grid stability. The comparative analysis of V2 GGlide (lowpass filter), V2 GSUN (moving average filter), and V2 GSmooth (ramp rate filter) reveals that all three methods successfully reduce power variance and enhance energy delivery to the grid, though their effectiveness strongly depends on the SoC of the storage system. V2 GGlide stands out for achieving the most significant variance reduction, reaching 22.24% at high SoC levels (above 80%), where the system efficiently absorbs large power fluctuations while delivering an additional 0.27 kWh of energy. This makes V2 GGlide particularly suitable for applications prioritizing maximum variance reduction and stability under favorable battery conditions. V2 GSUN, while less effective under low SoC conditions, remains a consistent performer with a variance reduction of up to 17.82% at SoC levels below 20% and improved energy delivery of 0.20 kWh under moderate SoC levels, making it a practical option for systems with intermediate energy availability. V2 GSmooth offers a balanced performance across all SoC conditions, achieving variance reductions comparable to V2 GSUN and demonstrating higher efficiency in energy delivery and battery utilization, particularly at low SoC levels, where it reduces variance by 17.74% while improving energy output by 0.12 kWh. This consistent performance across varying SoC levels makes V2 GSmooth a reliable choice for dynamic operational environments where storage availability fluctuates. A key outcome of this work is the critical dependence of power smoothing effectiveness on the SoC level, with optimal results obtained when the LI-ION BESS operates within a charge range of 20% to 80%. Outside this range, particularly at low SoC, the system's capacity to compensate for large power fluctuations is significantly limited, leading to increased variability and reduced energy delivery improvements. These findings confirm that maintaining efficient SoC management is essential for maximizing the benefits of power smoothing techniques and ensuring stable grid integration of intermittent PV energy. It is important to note in all the study cases that power smoothing techniques inherently result in slight deviations of the active power supplied by the renewable generator from its nominal value. However, this trade-off is outweighed by the significant benefits of reduced variability, which enhances grid stability and supports the integration of renewable energy sources into the grid. Finally, while the proposal successfully achieved its objectives, it also acknowledges certain limitations; for instance, the dependence on controlled laboratory conditions, which may not fully capture the complexities of real-world grid operations, especially in environments with higher renewable penetration and more diverse load profiles. Future work should focus on integrating these methods with advanced dynamic SoC management strategies and adaptive control systems, including predictive techniques and artificial intelligence-driven energy forecasting, to further enhance system performance. Additionally, incorporating hybrid energy storage solutions and validating these approaches in larger-scale microgrids will be critical for extending their applicability to real-world scenarios. Conceptualization, E.V.-A., P.A. and D.O.-C.; data curation, P.A., J.L.E. and D.O.-C.; formal analysis, E.V.-A., P.A. and D.O.-C.; funding acquisition, P.A. ; investigation, E.V.-A. and P.A. ; methodology, E.V.-A., P.A. and D.O.-C.; project administration, F.J.; resources, P.A. and F.J.; software, E.V.-A., P.A. and D.O.-C.; supervision, F.J.; validation, E.V.-A., P.A., E.A.-V. and D.O.-C.; visualization, E.V.-A., J.L.E. and E.A.-V.; writing--original draft, E.V.-A., P.A. and D.O.-C.; writing--review and editing, P.A.