Model-free predictive rotor current control of DFIGs based on an adaptive ultra-local model under nonideal power grids

The traditional control method of doubly fed induction generators (DFIGs) has poor robustness due to the excessive use of machine parameters, and does not fully consider the control conditions of nonideal power grids, resulting in serious fluctuations in current and power under grid disturbances. To solve these problems, model-free predictive rotor current control (MFPRCC) based on an ultra-local model is proposed in this article. The ultra-local model is adaptive because it can accurately emulate the overall structure of the system and estimate the total disturbance of the system in real time. Under a nonideal grid, the cascaded delayed signal cancellation (CDSC) modules are connected in series behind the outer power loop to extract the fundamental component of the rotor current reference. The proposed method is compared with the traditional model predictive rotor current control (MPRCC) method, and the effectiveness of the proposed method is verified on a 1.5 kW DFIG experimental platform. This article proposes a model-free predictive current control method based on an ultra-local model, which does not rely on machine parameters. The method has an excellent system robustness and a satisfactory control effect in a nonideal grid. The ultra-local model is applied, and the total disturbance of the system and the gain of the input voltages are estimated online in each sampling period. image