Optimization of harmonics with active power filter based on ADALINE neural network

Mostly the power quality issues in the distribution line system happen due to the presence of harmonics. Especially, the nonlinear loads such as power electronic converters, high-speed semi-conducting switches, and solid state drives were the major causes for harmonics in distorted power system signals. Moreover, the estimation of magnitude and the phase of this harmful harmonic interference are necessary. By taking in to consideration of all the above factors, this paper develops an efficient technique for harmonic estimation and detection of the renewable wind energy resources and elimination of these harmonics will also be done accordingly for getting desired output from wind energy. 8 bit inputs (4 + 4) are collected and used to generate the intended input set for ANN training. The proposed work develops an Adaptive Linear Neural Network (ADALINE) for the estimation of harmonics which is the novelty of this work. For making the harmonics content more negligible and to enhance the load power quality, an Active Power Filter (APF) is used. The novel control design is developed with a Pulse Width Modulation (PWM) control. In addition, feed forward networks (trained by back propagation algorithm) works like a hysteresis band comparator. An APF control design is developed with ADALINE network in which the load and current along with voltage will be analyzed and then the controller will be calculating the control signal by considering the reference compensation current. Afterwards, the power system is injected with compensating current. The simulation is carried out with Matlab-Simulink laboratory prototype is developed with Xilinux 3E Spartan FPGA board to verify the proposed control designs. The proposed work is compared with exiting method comprising Shunt Active Power Filters (SAPF) with ADALINE for the performance perspectives. This method was found to be effective in terms of many parameters such as load voltage, load current, voltage, reactive power, real power and especially THD value than those of the existing works which are considered. (C) 2019 Elsevier B.V. All rights reserved.