SCIG wind turbine wireless controlled using morphological filtering for power quality enhancement

In a renewable energy power system inside a smart grid environment, the use of wireless technologies for remote transmitting control information to the wind turbines requires modern techniques to improve the overall generated power quality and prevent damage to the turbines and converters. In this work, a robust wireless control system for a squirrel cage induction wind turbine connected to the power grid is proposed. The system employs convolutional coding and morphological filtering jointly to enhance the generated power quality by improving the robustness of the control system to the errors caused by the radio propagation channel. The performance is investigated in terms of total harmonic distortion and overall system response to verify the power quality delivered by the wind turbine to the grid. The satisfactory results endorse the operability and advantages of the proposed wireless control system.

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