Abstract
Wind energy conversion systems (WECSs) require a suitable control to maximise the power generated by wind turbines independently on the wind conditions. Variable-speed fixed-pitch wind turbines with doubly-fed induction generators (DGIG) are used in WECSs for their higher reliability and efficiency compared to variable-pitch wind turbine systems. This study proposes an effective control algorithm to maximise the efficiency of fixed-pitch wind turbines with DFIGs using particle swarm optimisation control to compensate for the errors in the estimation of the circuit parameters of the generator. The proposed control algorithm generates an optimal speed reference to optimise the mechanical power extracted from the wind and the optimal d -axis rotor current through stator reactive power management to minimise the electrical losses of the doubly-fed generator. The optimal speed reference is provided by a maximum power point tracking control below the rated wind speed and a soft-stalling control above the rated wind speed, while the optimal d -axis rotor current is searched by a particle swarm optimisation algorithm. The proposed control system has been verified by numerical simulations and it has been demonstrated that the energy generated for typical wind speed profiles is greater than that of a traditional control based on a model-based loss minimisation.
Highlights
Wind energy is one of the most attractive renewable energy for its large availability and high power density [1]
This study proposes an effective control algorithm to maximise the efficiency of fixed-pitch wind turbines with doubly-fed induction generator (DFIG) using particle swarm optimisation control to compensate for the errors in the estimation of the circuit parameters of the generator
The proposed control algorithm generates an optimal speed reference to optimise the mechanical power extracted from the wind and the optimal d-axis rotor current through stator reactive power management to minimise the electrical losses of the doubly-fed generator
Summary
Wind energy is one of the most attractive renewable energy for its large availability and high power density [1]. To improve the dynamic efficiency, it is preferable to use a fixed-pitch wind turbine with an active stall control, known as soft-stalling control, obtained with the speed control of the generator [9, 11, 12]. MPPT and minimum electric loss (MEL) controllers have been proposed to optimise the efficiency of the wind turbine when the electrical generator is a squirrel-cage induction generator [13]. This control can be extended to DFIGs, with the advantage of independent control of the shaft speed/torque and stator reactive power when a stator field oriented (SFO) vector control of the rotor converter is used [14]. This paper proposes a new optimal control that uses MPPT and a soft-stalling controller to obtain the optimal speed reference for the electrical generator and a PSO searching control to obtain the optimal ird reference for the SFO vector control
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