Shunt Active Power Filter Control using Radial Basis Function Neural Network

This paper presents a harmonics extraction algorithm using artificial intelligent method for shunt active power filter. Generally, Fourier Transform is used to analyze a distorted wave from power line and low pass filter is used to eliminate the fundamental wave before each harmonics component is detected. This conventional approach is difficult to implement due to the complicated process. In order to improve the processing speed and simplify harmonics detection process, the neural network algorithm proposed. The radial basis function neural network (RBFNN) type is utilized for controlling the injection compensation current of shunt active power filter (APF) for harmonics mitigation. The advantages of RBF over the other neural network models are simple structure where the activation function and learning speed can be increased Key WordsRBFNN, harmonics extraction, APF