Wind turbine control systems serve as the central intelligence of each turbine, managing functions such as blade pitch, yaw adjustments, energy conversion, and fault detection. . This study develops a robust nonlinear control, using an integral sliding mode control (ISMC) associated to an artificial neural network (ANN) approach for a variable-speed wind turbine (VSWT). At below rated speed of wind, the control aims to extract the maximum energy from the wind by the WT as. . This evolution calls for next-generation wind turbine control systems—a fusion of intelligent automation, digitalization, and adaptive control technologies.
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Any must match electricity production to consumption, both of which vary significantly over time. Energy derived from and varies with the weather on time scales ranging from less than a second to weeks or longer. is less flexible than, meaning it cannot easily match the variations in demand. Thus, without storage presents special challenges to .
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