Fuzzy Neural Optimized Fuzzy Logic Controller Based Dynamic Voltage Restorer for Power Quality Improvement with Non-linear Loads

Abstract

Recently a large attention has been focused on a power quality domain due to: disturbances caused by non-linear loads, Increase in number of electronic devices and growth of renewable energy sources. Power quality measures the fitness of electric power transmitted from generation to industrial, domestic and commercial consumers. At least 50% of power quality problems are of voltage quality type. In power system voltage sags, voltage distortion introduced by harmonics, and asymmetrical voltage are considered to be the most severe affecting power quality, because both utilities and consumers are affected by these disturbances. Different methods introduced to solve power problems but the custom power devices are the most effective and efficient methods, one of which is the use of the Dynamic Voltage Restorer (DVR). The main objectives of this research are to achieve more accuracy in compensating the voltage variations and reducing the total harmonics distortion (THD) to acceptable limits. Most of the researchers applied the control strategies to compensate the voltage disturbances in critical load but did not focus on the objective of reducing the total harmonics distortion (THD). In many sensitive loads such as, airport lighting system, medical equipment, auxiliary plant of power system, and adjustable speed drives., the level of the (THD) is more important, this research focuses on mitigating the harmonics to less than 3%. An adaptive controller like fuzzy neural optimized fuzzy logic controller is proposed to improve the performance of the DVR in injecting the required voltage to restore the load voltage to its nominal value under different voltage variations which are created by MATLAB/SIMULINK program for a period of 0.15s from 0.8s and kept till 0.95s.