Robust Predictive Rotor Current Control of a Doubly Fed Induction Generator Under an Unbalanced and Distorted Grid
Yongchang Zhang, Tao Jiang
Abstract
Under unbalanced and distorted grid conditions, the performance of conventional control methods for doubly fed induction generators (DFIGs) severely deteriorates, resulting in highly distorted stator and rotor currents. Furthermore, the performance can further degrade when the machine parameters used in such a controller differ from their actual values due to temperature, saturation and so on. To solve these problems, this paper proposes a robust predictive rotor current control (R-PRCC) scheme for a DFIG with multiple aims, even under unbalanced and distorted grid conditions. First, the reference value of the positive-sequence component of the rotor current is obtained from the outer power loop with the help of cascaded delayed signal cancellation (CDSC), which ensures the control aim of sinusoidal and balanced rotors currents. By investigating the relationship between stator currents and rotor currents, a new rotor current reference without using DFIG parameters can be obtained to satisfy multiple control aims, including sinusoidal and balanced stator currents, constant output active power and constant electromagnetic torque. Second, by introducing an extended state observer (ESO), the total disturbance caused by model uncertainty can be quickly estimated, and deadbeat control is further incorporated to achieve fast and accurate control of the rotor current. The proposed R-PRCC scheme is compared to conventional field-oriented control (FOC) and model predictive rotor current control (MPRCC). Simulated and experimental results are obtained for a 1.5-kW laboratory. The DFIG system confirms the effectiveness of the proposed method.