Wind energy is a pivotal technology in the global shift toward sustainable power generation. This research tackles a key challenge in wind turbine systems: managing mechanical speed variations that affect performance, stability, and operational longevity. Using a simplified wind turbine model, we developed an intelligent proportional-integral i-PI controller to achieve precise mechanical speed regulation and enhance energy extraction efficiency. Our study investigates current wind turbine technological challenges and introduces a novel intelligent control approach. The proposed i-PI controller demonstrated a 25% reduction in tracking error compared to a conventional PI controller during fluctuating wind conditions, ensuring more accurate speed regulation. Additionally, the system achieved a 15% increase in power output across varied operational scenarios, reflecting improved energy extraction efficiency. By maintaining the tip-speed ratio λ within 5% of the theoretical optimum, compared to a 12% deviation for the PI controller, our methodology ensures optimal operation even under turbulent wind conditions. Implementation testing also indicated improved stability, with the i-PI controller better handling sudden wind variations, potentially reducing mechanical stress and extending component lifespan. These findings, contribute to advancing wind energy technologies and intelligent control methodologies, demonstrating that adaptive control strategies can significantly enhance renewable energy system performance and operational reliability in this preliminary investigation.