Improved Maximum Power Point Tracking Control for D-PMSG Systems: Fuzzy Gradient Step Approach

Abstract

This study introduces an enhanced Maximum Power Point Tracking (MPPT) control strategy for Direct Drive Permanent Magnet Synchronous Generators (D-PMSG) utilizing a Fuzzy Gradient Step Approach. By comparing with traditional MPPT methodologies, this approach demonstrates significant improvements in tracking accuracy, efficiency, and response time to fluctuating environmental conditions. The fuzzy logic control method adapts dynamically, optimizing power output under variable wind speeds. The comparative analysis reveals that our method not only surpasses conventional techniques in performance but also offers a cost-effective solution with less complexity. Implications of these advancements suggest potential applications in optimizing wind energy systems, enhancing the viability of renewable energy sources. By examining the relationship between Boost duty cycle changes and wind turbine output characteristics, a fuzzy gradient step hill-climbing search method is proposed to calculate the wind turbine output speed in order to improve the maximum power point tracking control performance of the direct-drive permanent magnet wind power generation system. The fuzzy controller employs the duty cycle of the Boost converter as its output quantity and its input quantity to accomplish the maximum power point tracking control of the wind turbine. A model was developed and verified through simulation for use in system modeling. The results show that the fuzzy gradient step hill-climbing search approach is more effective at regulating the maximum power point tracking control of the direct-drive permanent magnet wind power producing system than the traditional variable step-size hill-climbing search algorithm. This research paves the way for future exploration in smart grid integration and scalability of fuzzy logic-based MPPT controllers, marking a pivotal step towards sustainable energy solutions.