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        PSO Based Fractional Order PI Controller and ANFIS Algorithm for Wind Turbine System Control and Diagnosis

        Labed Nasreddine,Attoui Issam,Makhloufi Salim,Bouraiou Ahmed,Bouakkaz Mohammed Salah 대한전기학회 2023 Journal of Electrical Engineering & Technology Vol.18 No.3

        In the recent years, the usage of fossil fuels presents the major source of air pollutants and greenhouse gases. Renewable energies essentially wind, solar, geothermal, waves, biomass, hydrogen and so on, are used as an alternative source of fossil energy to overcome these problems. Among the several renewable energy sources, the wind energy is one of the primary types of renewable energy that can be effectively connected to the grid. However, power generation management, control and condition monitoring of wind turbine systems represent major challenges to the researchers in this field. Therefore, this paper considers these issues and demonstrates effective techniques of power generation management, system control and condition monitoring. A hybrid super-capacitor-battery energy storage system is used to support the power generation of the wind turbine under wind speed variations and grid demand changes using two DC/DC converters. Fractional Order PI Controllers tuned using particle swarm optimization PSO algorithm, are proposed in order to control the proposed system. The control strategy guarantees the stability of the wind turbine system in healthy and faulty operating conditions. Based on the stator reactive power signal of the DFIG, the proposed diagnostic strategy involves a data-driven method using the FFT algorithm for extracting the frequency feature parameters. The Adaptive Neuro-Fuzzy Inference System ANFIS is used for automatically detecting and classifying the rotor and stator faults of the DFIG. Finally, simulation results validate the effectiveness and the reliability of the proposed methods.

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