Multiple AI based Controlling Techniques for Power Filter Output Quality Improvement

Abstract

The excessive of power electronics devices in distribution system has evolved the problem of power quality. This work represents the effective solution of shunt active power filter for eliminating the harmonics to maintain the quality of utility power supply. In the proposed scheme shunt active filter acts as a voltage source and eliminates harmonics by injecting equal but opposite harmonics components at the point of common coupling. Simulation of shunt active filter based on instantaneous reactive has been achieved in the MATLAB/SIMULINK environment. The controllers are being designed with the objective of reducing the THD% in voltage and current available at the nonlinear load terminal of the system. The controller incorporated optimization algorithms based on the artificial intelligence techniques as well. The comparative analysis of the effectiveness and efficiency of the controllers in improving the quality factors has been carried out. The distortion level in the output voltage waveforms in both the cases being fed to the load when compared, it is found that proposed hybrid structure of control for the filter is more effective in reducing the distortion as compared to standard PQ theory based architecture. The study concluded that the total harmonic distortion in the voltage output waveform being fed to the load using only PQ theory based online learning algorithm is found to be 1.59 % while in case of the output voltage at the load terminal from the power filter using proposed hybrid algorithm comprising of NN learning with CSA optimizing control and PQ_RLS algorithm for THD reduction the THD% level is 0.43 %.