Adaptive Neural Network with Heuristic Learning Rule for Series Active Power Filter


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Abstract


A new design for controller of series active power filter (APF) is presented in this paper. The goal of the proposed system is to compensate voltage harmonics in power distribution system. The proposed control system utilizes adaptive neural network with heuristic learning approach. The present voltage harmonics on the supply side are estimated and extracted by the neural network based controller. Moreover, the heuristic learning rule optimizes learning rate value of the neural network that results in an accurate estimation of harmonic components and a very fast response time of the APF. Operating performance of the designed three-phase series APF was evaluated by MATLAB-Simulink tool environment. The simulation works were conducted to examine the APF’s abilities under low voltage distribution conditions. Simulation results demonstrate the ability of the proposed series APF in reduction of harmonic distortion in the supply voltage with an overall initial THD of 87% down to 3.3% and can adapt quickly to variations of distortions in system operating conditions.
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Keywords


Series Active Power Filter; Heuristic Learning Rule; Harmonic; Neural Network; Power Quality

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