Title :
Predictive control of active power filters
Author :
Marks, J.H. ; Green, T.C.
Author_Institution :
Dept. of Electr. & Electron. Eng., Imperial Coll. of Sci., Technol. & Med., London, UK
fDate :
6/23/1905 12:00:00 AM
Abstract :
A novel technique 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 DC link smoothing filter is presented. This allows for accurate calculation of cancellation references for series and shunt APFs 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 calculate the mean dq-axis input to the rectifier without filtering. This is the critical stage in separating the harmonic distortion from fundamental current or voltage. The technique is developed using simulation data for both shunt and series APFs and validated with experimental results
Keywords :
active filters; neural nets; power harmonic filters; power system harmonics; predictive control; rectifying circuits; ANN predictor; DC link smoothing filter; artificial neural network predictor; cancellation references; control system bandwidth; distorted input current; distorted input voltage; harmonic distortion separation; mean dq-axis input; power rating reduction; series active power filters; shunt active power filters; steady-state conditions; transient conditions; uncontrolled three-phase bridge rectifier; Active filters; Artificial neural networks; Bridge circuits; Control systems; DC generators; Predictive control; Rectifiers; Smoothing methods; Steady-state; Voltage;
Conference_Titel :
Power Electronics Specialists Conference, 2001. PESC. 2001 IEEE 32nd Annual
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-7067-8
DOI :
10.1109/PESC.2001.954315