Open AccessStability Enhancement by Comparative Analysis of AI Techniques in Power System Stablizer Integrated With Hybrid System
Author(s) -
Harsh Vardhan Singh,
Ranjeeta Khare
Publication year - 2019
Publication title -
smart moves journal ijoscience
Language(s) - English
Resource type - Journals
ISSN - 2582-4600
DOI - 10.24113/ijoscience.v5i6.245
Subject(s) - particle swarm optimization , control theory (sociology) , total harmonic distortion , matlab , electric power system , artificial neural network , waveform , hybrid system , voltage , power (physics) , hybrid power , computer science , distortion (music) , engineering , electronic engineering , control (management) , physics , algorithm , electrical engineering , artificial intelligence , amplifier , cmos , quantum mechanics , machine learning , operating system
Hybrid system has been modeled in MATLAB/SIMULINK environment which is then integrated with two generators based power system. The work has done over analysis of THD level in voltage output from the hybrid system with various controls being proposed for the power system stabilizer. Various controls like PI-Hysteresis, particle swarm optimization (PSO) and PSO with neural network (NN) have been implemented for comparative study. It was found that the distortion level in voltage output waveform was least in stabilizer having PSO-NN control which is 3.36%. Also the active power enhancement reached a whooping value of 9.4 KW from the hybrid system.