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  • Open Access


    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) algorithm for the rotor and… More >

  • Open Access


    Fractional-Order Control of a Wind Turbine Using Manta Ray Foraging Optimization

    Hegazy Rezk1,2,*, Mohammed Mazen Alhato3, Mohemmed Alhaider1, Soufiene Bouallègue3,4

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 185-199, 2021, DOI:10.32604/cmc.2021.016175

    Abstract In this research paper, an improved strategy to enhance the performance of the DC-link voltage loop regulation in a Doubly Fed Induction Generator (DFIG) based wind energy system has been proposed. The proposed strategy used the robust Fractional-Order (FO) Proportional-Integral (PI) control technique. The FOPI control contains a non-integer order which is preferred over the integer-order control owing to its benefits. It offers extra flexibility in design and demonstrates superior outcomes such as high robustness and effectiveness. The optimal gains of the FOPI controller have been determined using a recent Manta Ray Foraging Optimization (MRFO) algorithm. During the optimization process,… More >

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