A Modified EHO Algorithm Utilized DPFC for Power Quality Enhancement in Smart Grid

Abstract

In the study the modified Elephant Herd Optimization (EHO) algorithm is developed and designed by utilizing the distributed power flow controller (DPFC) for improving power quality (PQ) in smart grid (SG). The modification of the EHO algorithm is performed based on the Recurrent Neural Network (RNN) algorithm. The novelty in this proposed study is the enhancement of the PQ in SG from the disturbances occurred power system controller utilized the DPFC. Initially, the proposed system power flow is evaluated and the Multi Wavelet Transform (MWT) is employed to feature extraction process of the power parameters for PQ disturbances. If the output signal has any disturbances then the output signal is controlled by the proposed controller based DPFC. The proposed algorithm is employed to retain the sustained DC-link voltage of DPFC by controlling the output voltage to improve the PQ. Then the implementation process is made by the Matlab/Simulink simulation platform. The capability of the proposed system is based an evaluation of the output response and the comparative analysis with some different techniques like PSO, BAT and CFA-PSO algorithm.