The inherent time-varying nature of the wind farm power causes undesired voltage flicker in the power network. In order to mitigate the flicker to enhance the performance of the wind power system with very fast dynamics, the static VAr compensator (SVC) is utilized. However, the SVC operates with some delays which negatively affects its performance. This persuades us to predict the reactive power of the wind farm to compensate for the real-world delay. The predicted reactive power is then utilized in the SVC. Therefore, this paper develops a novel fuzzy one-step-ahead prediction approach for the wind farm reactive power. The proposed fuzzy prediction uses a Takagi-Sugeno (TS) fuzzy representation whose unknown parameters are tuned online based on an extended Kalman filter (EKF). The wind farm is modeled as a time-varying current source which its amplitude and phase change every 0.01 s. A large set of the actual data of a wind farm in Manjil, Iran is gathered and directly utilized in the simulation process. Several flicker indices are calculated to evaluate the proposed prediction method. The obtained results show the performance enhancement and flicker mitigation of the suggested power scheme.

风电场电力固有的时变特性会导致电网中出现不希望的电压闪烁。为了减轻闪烁以提高具有非常快动态的风力发电系统的性能，使用静态无功补偿器（SVC）。然而，SVC 运行时会有一些延迟，这对其性能产生负面影响。这说服我们预测风电场的无功功率以补偿现实世界的延迟。然后在 SVC 中使用预测的无功功率。因此，本文开发了一种新的风电场无功模糊单步提前预测方法。提出的模糊预测使用 Takagi-Sugeno (TS) 模糊表示，其未知参数基于扩展卡尔曼滤波器 (EKF) 在线调整。风电场被建模为时变电流源，其幅值和相位每 0.01 秒变化一次。伊朗曼吉尔风电场的大量实际数据被收集并直接用于模拟过程。计算了几个闪烁指数来评估所提出的预测方法。获得的结果显示了建议的电源方案的性能增强和闪烁减轻。