A novel particle swarm optimisation technique to improve energy efficiency of doubly-fed induction generators for wind turbines

Wind energy conversion systems requires a suitable control to maximise the power generated by wind turbines independently on the wind conditions. Variable-speed fixedpitch wind turbines with doubly-fed induction generators are used in WECSs for their higher reliability and efficiency compared to variable-pitch wind turbine systems. This paper proposes an effective control algorithm to maximise the efficiency of fixed-pitch wind turbines with doubly-fed induction generators using particle swarm optimization 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 doublyfed 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.