Abstract
This paper presents a new maximum-power-point-tracking (MPPT) controller in wind power generation using artificial neural networks (ANN) in order for making the wind turbine function in optimum working point and get high efficiency of wind energy conversion at different conditions. The algorithm uses fully connected recurrent neural network and is trained online using real-time recurrent learning (RTRL) algorithm in order to avoid the oscillation problem in wind-turbine generation systems. It generates control command for speed of the rotor side converter using optimal algorithm to enable the control system in order to track the maximum power point. The rotor speed and wind-turbine torque are the inputs of the networks, and the command signal for the rotor speed of wind turbine is the output. Simulation results verify the performance of the proposed algorithm.
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