Neurofuzzy Power System Stabilizer

Author

Chaturvedi, D.K. ; Malik, O.P.

Author_Institution

Fac. of Eng., Dept. of Electr. Eng., Dayalbagh Educ. Inst., Agra

Volume

23

Issue

3

fYear

2008

Firstpage

887

Lastpage

894

Abstract

An adaptive fuzzy logic power system stabilizer (AFPSS) consisting of a generalized neuron (GN)-based predictor and a fuzzy logic controller (FLC) is described. The inference mechanism of the FLC is represented by a rule-base and a database. Two parameters, decided on the basis of the GN-predictor output and the current system conditions, are used to tune the AFPSS. This mechanism of tuning makes the fuzzy logic-based power system stabilizer adaptive to changes in the operating conditions. Therefore, variation in the system response, under a wide range of operating conditions, is less compared to the system response with a fixed-parameter conventional PSS. The performance of the AFPSS has been tested by simulation and experimental studies.

Keywords

control engineering computing; fuzzy control; inference mechanisms; neurocontrollers; power engineering computing; power system control; power system stability; adaptive fuzzy logic power system stabilizer; fuzzy logic controller; generalized neuron-based predictor; inference mechanism; neurofuzzy power system stabilizer; Adaptive control; Control systems; Databases; Fuzzy logic; Fuzzy systems; Inference mechanisms; Neurons; Power system simulation; Power systems; Programmable control; Artificial neural networks (ANN); fuzzy logic; generalized neuron; intelligent controllers; neurofuzzy; power system stabilizer (PSS);

fLanguage

English

Journal_Title

Energy Conversion, IEEE Transactions on

Publisher

ieee

ISSN

0885-8969

Type

jour

DOI

10.1109/TEC.2008.918633

Filename

4603061