一种改进的分数阶开路电压MPPT方法用于独立光伏系统中快速精确的MPP跟踪

In this research it is essential to use a maximum power point tracking (MPPT) method to capture the maximum power from solar panels in varying weather conditions. Instead of focusing solely on individual optimization MPPT algorithms, current studies now explore combining different methods for better results. This study introduces a hybrid MPPT approach that combines the Musical Chairs Algorithm (MCA) and Fractional Open Circuit Voltage (FOCV). By using one decision variable, this technique simplifies the process and reduces the time needed to reach optimal performance. Unlike FOCV’s limitations in power output and tracking efficiency, this new approach offers improved outcomes. The effectiveness of this method is tested under irradiance conditions like gradual changes in irradiance condition, sinusoidal patterns, and real irradiance profile using MATLAB/SIMULINK. The simulation findings reveal that this new method surpasses studied methods by achieving faster convergence within 0.08 s and slightly higher efficiency rates of up to 99.8% under different irradiance conditions. The study demonstrates that integrating MCA with FOCV improves efficiency by nearly 7% while reducing oscillations during steady-state operation. Moreover, this paper provides a comprehensive assessment of various MPPT methods from the literature, examining factors such as controlled variable, complexity, tracking speed, and efficiency. Furthermore, this innovative method promises response times, better efficiency levels and reduced oscillations compared to other MPPT approaches.