Performance enhancement of UPQC based on optimized GBSSA hybrid fuzzy controller with EPLL

被引:0
|
作者
Monikandan, A. S. [1 ]
Kumar, C. Agees [1 ]
机构
[1] Arunachala Coll Engn Women, Dept Elect & Elect Engn, Vellichanthai, India
关键词
UPQC; enhanced PLL; GBSSA; hybrid fuzzy controller; power quality issues; POWER-QUALITY; CONTROL STRATEGIES; IMPROVEMENT; 3-PHASE;
D O I
10.3233/JIFS-213263
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this research, UPQC (Unified Power Quality Conditioner) with optimized hybrid fuzzy controller based GBSSA (Gaussian Barebone SalpSwarm Algorithm) withEPLL(Enhanced Phase Locked Loop) have been proposed for power quality enhancement in power distribution networks. Using the proposed method, the difficulties in major of the power distribution system networks can be solved, related to power quality issues. GBSSA has been employed in this research, to improve solution accuracy and optimization efficiency. Given that, it is permissible to add some extra time cost to acquire a better solution, based on the Non-Free Lunch (NFL) theory, and that the time consumption of function evaluation is rather large, when addressing actual optimization problems, the extra time consumption can be overlooked to some extent. The EPLL control method improves the standard PLL, by reducing its fundamental flaw, which is the occurrence of main frequency errors, as well as double frequency errors. It controls the DC-bus voltage of unified power quality conditioners, during supply voltage and load voltage turbulences. The proposed UPQC control technique has been found to be resilient, to a variety of source and load perturbations, including unbalanced, transient distorted supply, voltage sag, unbalanced load and voltage swell. The proposed optimized GBSSA hybrid fuzzy controller with EPLL has been proven to be more effective in reducing the THD (Total Harmonic Distortion) to 3.22%. Moreover, comparative analysis with a conventional TSF-PLL has been performed with that of Takagi-Sugeno fuzzy controller and implemented using MATLAB (MATrix Laboratory).
引用
收藏
页码:7199 / 7211
页数:13
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