Paper Info
Title
Adaptive power system stabilizer using ANFIS and genetic algorithms
Abstract
This paper presents an adaptive Power System Stabilizer (PSS) using an Adaptive Network Based Fuzzy Inference System (ANFIS) and Genetic Algorithms (GAs). Firstly, genetic algorithms are used to tune a conventional PSS on a wide range of operating conditions and then, the relationship between these operating points and the PSS parameters is learned by the ANFIS. The ANFIS optimally selectes the classical PSS parameters based on machine loading conditions. The proposed stabilizer has been tested by performing nonlinear simulations using a synchronous machine-infinite bus model. The results show the robustness and the capability of the stabilizer to enhance system damping over a wide range of operating conditions and system parameter variations.
Year
DOI
Venue
2005
10.1007/11494669_138
IWANN
Keywords
Field
DocType
genetic algorithms,fuzzy systems,power systems,algorithm design and analysis,mathematical model,adaptive systems,control systems,genetic algorithm,operant conditioning,synchronous machine
Adaptive system,Computer science,Control theory,Electric power system,Robustness (computer science),Control system,Adaptive neuro fuzzy inference system,Fuzzy control system,Permanent magnet synchronous generator,Genetic algorithm
Conference
Volume
ISSN
ISBN
3512
0302-9743
3-540-26208-3
Citations 
PageRank 
References 
2
0.49
5
Authors
2
Name
Order
Citations
PageRank
Jesús Fraile-Ardanuy1418.99
Pedro J. Zufiria27715.27