Fault-Tolerant Control for SSSC Using Neural Networks and PSO

Author

Qiao, Wei ; Harley, Ronald G. ; Venayagamoorthy, Ganesh K.

Author_Institution

Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA

fYear

2006

fDate

Oct. 29 2006-Nov. 1 2006

Firstpage

952

Lastpage

958

Abstract

This paper presents a fault-tolerant indirect adaptive neuro-controller (FTNC) for controlling a static synchronous series compensator (SSSC), which is connected to a power network. The FTNC consists of a sensor evaluation and restoration scheme (SERS), a radial basis function neuro-identifier (RBFNI) and a radial basis function neuro-controller (RBFNC). The SERS is designed using the auto-associative neural networks (auto-encoder) and the particle swarm optimizer (PSO). This FTNC is able to provide efficient control to the SSSC when single or multiple crucial sensor measurements are unavailable. The validity of the proposed FTNC model is examined by simulations in PSCAD/EMTDC environment

Keywords

fault tolerance; neurocontrollers; particle swarm optimisation; power engineering computing; radial basis function networks; sensors; static VAr compensators; FTNC; PSCAD/EMTDC environment; PSO; RBFNC; RBFNI; SERS; SSSC; fault-tolerant indirect adaptive neuro-controller; neural networks; particle swarm optimizer; power network; radial basis function neuro-controller; radial basis function neuro-identifier; sensor evaluation-restoration scheme; synchronous series compensator; Adaptive control; Control systems; Fault tolerance; Intelligent sensors; Neural networks; PSCAD; Particle swarm optimization; Power system modeling; Power system transients; Programmable control;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Systems Conference and Exposition, 2006. PSCE '06. 2006 IEEE PES

Conference_Location

Atlanta, GA

Print_ISBN

1-4244-0177-1

Electronic_ISBN

1-4244-0178-X

Type

conf

DOI

10.1109/PSCE.2006.296441

Filename

4075880