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    Integration of Wind and PV Systems Using Genetic-Assisted Artificial Neural Network

    E. Jessy Mol*, M. Mary Linda

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1471-1489, 2023, DOI:10.32604/iasc.2023.024027

    Abstract The prominence of Renewable Energy Sources (RES) in the process of power generation is exponentially increased in the recent days since these sources assist in minimizing the environmental contamination. A grid-tied DFIG (Doubly Fed Induction Generator) based WECS (Wind Energy Conversion System) is introduced in this work, in which a Landsman converter is implemented to improvise the output voltage of PV without any fluctuations. A novel GA (Genetic Algorithm) assisted ANN (Artificial Neural Network) is employed for tracking the Maximum power from PV. Among the rotor and grid side controllers, the former is implemented by combining the stator flux with… More >

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