Advancing wind energy conversion: smart maximum power point based on M5-Pruned algorithm for enhanced wind energy production

This paper proposes a powerful smart algorithm in energy production engineering, optimizing wind turbine efficiency to meet industrial needs for sustainable energy via a novel maximum power point tracking (MPPT) strategy based on an advanced M5-Pruned algorithm under real-world wind conditions. Slow response to wind speed variations, limited applicability, sensitivity to system parameters, significant ripples, limited efficiency in low wind speeds, and complex structure are major drawbacks of traditional techniques in wind energy. The proposed M5-Pruned algorithm overcomes these obstacles with its intelligent prediction capabilities, fast dynamic response, accurate tracking, and adaptation to sudden changes. In rigorous simulations under real variable wind speeds, the performance of the M5-Pruned model is compared with traditional proportional-integral (PI) and fuzzy logic controller (FLC) methods, where the M5P model outperformed with lower total harmonic distortion (THD) values of 1.83% compared to 1.93% (PI) and 1.92% (FLC). The findings demonstrate a substantial increase in energy efficiency, paving the way for smarter, more sustainable and harnessed wind energy.