Artificial Intelligence-based MPPT Techniques in Wind Energy Systems: A Literature Review

The global opportunity to accelerate the world's renewable energy in future is technological progress. Today, artificial intelligence (AI) is used to drive the fastest revolution in technology. Thus, the highest possible level of energy conversion efficiency is required for wind turbines in order to fully use wind power. This paper introduces an overview of AI-based Maximum-Power-Point- Tracking (MPPT) for wind energy systems (WES). Given that wind energy conversion systems (WECS) are becoming increasingly complex and unexpected changing in wind speed conditions. Indeed, working conditions have a major impact on yield. Achieving the ideal yield is typically difficult. For this reason, MPPT controllers are attracting a lot of attention. This review provides a thorough analysis of both Artificial Neural Networks (ANN) and Fuzzy Logic (FL) used in WES. And identifies the approaches used most frequently to provide the best possible yield in many situations. Both ANN and FL may be utilised instead of more traditional approaches for control and optimisation, for which the approaches are collected and analysed based on the application. Both techniques in this area and its potential developments are statistically presented. A thorough bibliography is done, ideas for further study are offered, and a number of difficulties have been risen. Ultimately, future research in wind generation systems should find this platform helpful to academics, energy planners, and politicians.