In this chapter, we present a comparative study of conventional Indirect
Power Control (IDPC) algorithm of DFIG-Wind turbine in grid-connection mode,
using PI and PID controllers via Maximum power point tracking (MPPT) strategy.
Firstly, the conventional IDPC based on PI controllers will be described using
simplified model of DFIG through stator flux orientation and wind-turbine model. The
MPPT strategy is developed using Matlab/Simulink® with two wind speed profiles in
order to ensure the robustness of wind-system by maintaining the Power coefficient
(Cp) at maximum value and reactive power at zero level; regardless unexpectedF wind
speed variation. Secondly, the rotor side converter (RSC) and Grid side converter
(GSC) are illustrated and developed using Space vector modulation (SVM) in order to
minimize the stress and the harmonics and to have a fixed switching frequency. In this
context, the switching frequency generated by IDPC to control the six IGBTs of the
inverter (RSC), and this control algorithm works under both Sub- and Supersynchronous
operation modes and depending to the wind speed profiles. The quadrants
operation modes of the DFIG are described in details using real DFIG to show the
power flow under both modes (motor and generator in the four (04) quadrants. Finally,
the conventional IDPC have several drawbacks as: response time, power error and
overshoot. In this context, the PID and MRAC (adaptive regulator) controllers are
proposed instead of the PI to improve the wind-system performances via MPPT
strategy with/without robustness tests. The obtained simulation results under
Matlab/Simulink® show high performances (in terms of power error, power tracking
and response time) in steady and transient states despite sudden wind speed variation,
whereas big power error and remarkable overshoot are noted using robustness tests, so
the proposed IDPC can not offer big improvement under parameter variation.
Keywords: Indirect Power Control (IDPC) algorithm, Maximum power point
tracking (MPPT) strategy, Model Reference Adaptive Control (MRAC), Space
vector modulation (SVM).
