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    Machine Learning Controller for DFIG Based Wind Conversion System

    P. Srinivasan1,*, P. Jagatheeswari2

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 381-397, 2023, DOI:10.32604/iasc.2023.024179

    Abstract Renewable energy production plays a major role in satisfying electricity demand. Wind power conversion is one of the most popular renewable energy sources compared to other sources. Wind energy conversion has two major types of generators such as the Permanent Magnet Synchronous Generator (PMSG) and the Doubly Fed Induction Generator (DFIG). The maximum power tracking algorithm is a crucial controller, a wind energy conversion system for generating maximum power in different wind speed conditions. In this article, the DFIG wind energy conversion system was developed in Matrix Laboratory (MATLAB) and designed a machine learning (ML) More >

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