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In this study. based on the slope of the wind-turbine mechanical power versus rotation speed. a novel MPPT algorithm using neural network compensator is proposed to avoid the oscillation problem and effect of uncertain parameters in wind-turbine generation systems. Naturally. the characteristics of the wind-turbine rotation speed is determined by the wind speed and air density conditions. thereby the technologies of changing the location of the maximum power point must be developed in the applications of maximum-power-point-tracking (MPPT) control in order to make the wind-turbine generator get the optimal efficiency from wind energy at different operating conditions. In this study. the uncertainties in wind-turbine generation systems are compensated by a neural network and the duty cycle of the boost dc dc converter is determined by a PI controller. the parameters of which is determined by a genetic algorithm (GA) with the help of MATLAB. From the simulation results. the validity of the proposed MPPT controller can be verified under variations of wind speed. ambient air density. and the load electrical characteristics.
