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A research on conventional and modern algorithms for maximum power extraction from wind energy conversion system: a review.

Muhammad Zeeshan MalikMazhar Hussain BalochMehr GulGhulam Sarwar KaloiSohaib Tahir ChauhdaryAli Asghar Memon
Published in: Environmental science and pollution research international (2020)
In the last few decades, wind energy has become a significant source of the renewable energy system, and it is essential to use wind energy for generating power and run the wind turbine system (WTs) at a higher level. With the rapid penetration of wind energy in the distributed generation system (DGS) and isolated micro-grid (MG), the WT runs at its optimal energy conversion output. For this, WT has to track or drive at the optimal power point tracking algorithm. However, various publications are available on MPPT algorithms for wind energy system (WES) applications, making a choice on exact trackers for a particular algorithm because each tracker has its advantages and disadvantages. Therefore, our primary goal is to review and evaluate the exact tracking algorithm for WES applications in this manuscript. To introduce the power controller, it is essential to track maximum power despite wind energy results. Besides, many algorithms have been evaluated, and their maximum output is achieved compared to their performance. This research paper will help researchers provide an accurate reference for future recommendations by selecting the best tracking algorithms in WES.
Keyphrases
  • machine learning
  • deep learning
  • density functional theory
  • sensitive detection