Neural MPPT of Variable Pitch Wind Generators with Induction Machines in a Wide Wind Speed Range

--This paper proposes a maximum power point tracking (MPPT) technique for variable-pitch wind generators with
induction machines (IMs), which can suitably be adopted in both
the maximum power range and the constant-power range of
the wind speed. To this aim, an MPPT technique based on the
growing neural gas (GNG) wind turbine surface identification
and corresponding function inversion has been adopted here to
cover also the situation of variable-power region. To cope with the
constant-power region, the blade pitch angle has been controlled
on the basis of the closed-loop control of the mechanical power
absorbed by the IM. The wind speed is then estimated in the
constant-power region on the basis of the actual position of the
blade pitch angle. The proposed methodology has been verified
both in numerical simulation and experimentally on a properly
devised test setup. In addition, a comparison between the proposed
approach and the previously developed GNG-based MPPT has
been performed on a real wind speed profile. Finally, the effect of
the torsional stiffness of the mechanical transmission system has
been analyzed.