Abstract
A novel technique is presented for generation of a contemporary estimate of the fundamental component of the distorted input current or voltage to an uncontrolled three-phase bridge rectifier with a DC link smoothing filter. This allows for accurate calculation of cancellation references for series and shunt active power filters (APF) operating under steady-state and transient conditions. Improved transient performance allows for reduction of the power rating and control system bandwidth of an APF. An artificial neural network (ANN) predictor has been used to directly calculate the mean dq-axis input to the rectifier without filtering. This is a critical stage in separating harmonic distortion from fundamental current or voltage. The technique is developed using simulation data for both series and shunt APFs and validated with experimental results. The predictive harmonic identifier shows good steady-state performance and excellent transient performance that far exceeds that of a conventional identifier using time-domain or frequency-domain filtering.
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