摘要
Fast fluctuations in wind farm power produce voltage flicker in the network.One way to mitigate the flicker is to place a static VAr compensator(SVC).Due to the operating delay of SVCs,it is essential to predict the wind farm reactive power.Here,a novel fuzzy nonlinear modeling approach is suggested and used in the one-step-ahead prediction of the power characteristics.The base of the developed fuzzy modeling is the Takagi-Sugeno fuzzy representation and a dual-unscented Kalman filter(D-UKF).In other words,a nonlinear TS fuzzy system is trained online via the D-UKF.The forecasted value is used as the SVC’s reference signal.A large amount of actual data gathered from a wind farm is used for the performance evaluation.This data is collected in winter and summer for different climate situations.Using the actual data,a current source with changing amplitude and phase which is updated every half-cycle,is used to model the wind farm.Numerical results,including the flicker indices,confirm the improvement in the SVC’s performance.
