Real-Coded Genetic Algorithm and Fuzzy Logic Approach for Real-Time Load-Tracking Performance of an Autonomous Power System

被引：0
|
作者：
Banerjee, Abhik [1 ]
Mukherjee, V. [2 ]
Ghoshal, S. P. [3 ]
机构：
[1] Asansol Engn Coll, Dept Elect Engn, Asansol, W Bengal, India
[2] Indian Sch Mines, Dept Elect Engn, Dhanbad 826004, Jharkhand, India
[3] Natl Inst Technol, Dept Elect Engn, Durgapur, W Bengal, India
来源：
SWARM, EVOLUTIONARY, AND MEMETIC COMPUTING, PT II (SEMCCO 2013) | 2013年 / 8298卷
关键词：
Automatic voltage regulator; load-tracking performance; optimization; real-coded genetic algorithm; Sugeno fuzzy logic;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper focuses on the application of real-coded genetic algorithm (RGA) to determine the optimal controller parameters of an autonomous power system model for its load tracking performance analysis. To determine the real-time parameters of the studied model, Sugeno fuzzy logic (SFL) is used. RGA is applied to obtain the controller parameters for transient response analysis under various operating conditions and fuzzy logic is applied to develop the rule base of the SFL model. The developed fuzzy system gives the on-line controller parameters for different operating conditions. Time-domain simulation of the investigated power system model reveals that the proposed RGA-SFL yields on-line, off-nominal controller parameters, resulting in on-line terminal voltage response. To show the efficiency and effectiveness of RGA, binary coded genetic algorithm is taken for the sake of comparison.
引用
收藏
页码：119 / 131
页数：13
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