Abstract- This paper presents a novel maximum-power-point
tracking (MPPT) algorithm in wind-turbine generation
systems using neural network compensator based on the slope
of the wind-turbine mechanical power versus rotation speed
to avoid the oscillation problem and effect of uncertain
parameters. Because the characteristics of the wind-turbine
rotation speed is determined by the wind speed and air
density conditions, the technologies of changing the location
of the maximum power point must be developed in the
applications of 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, the duty cycle of dc/dc
converter is determined by a PI controller, and the
parameters is determined by a genetic algorithm with the
help of MATLAB. From the simulation results, the validity of
the proposed MPPT controller can be verified under
variations of wind speed, air density, and the load electrical
characteristics in wind-turbine generator systems.
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