GA neuro-fuzzy damping control system for UPFC to enhance power system transient stability

Author

Khan, Laiq ; Ahmed, N. ; Lozano, Carlos

Author_Institution

Fac. of Electron. Eng., GIK Inst. of Eng. Sci. & Technol., Topi, Pakistan

fYear

2003

fDate

8-9 Dec. 2003

Firstpage

276

Lastpage

282

Abstract

A hybrid GA-neurofuzzy damping control system for a unified power flow controller (UPFC) is proposed to enhance the transient and dynamic stability of a power system. The neurofuzzy damping controller is configured by employing a five layer feedforward fuzzy neural network. A novel "grandparenting" technique is employed for seeding the initial population to hasten the convergence speed of micro-GA. Also, a parallel micro-GA scheme is used to speed up the genetic algorithm search-space surfing process. The performance of the resulting neurofuzzy-based UPFC is validated in a multi-machine power system environment by means of digital simulation.

Keywords

feedforward neural nets; fuzzy control; fuzzy logic; fuzzy neural nets; genetic algorithms; power system dynamic stability; power system transient stability; power transmission control; GA neuro-fuzzy damping control system; UPFC; damping control system; feedforward fuzzy neural network; feedforward neural network; flexible ac transmission systems; fuzzy control; genetic algorithm search-space surfing process; grandparenting technique; multi-machine power system setup; parallel micro-GA scheme; power system dynamic stability; power system transient stability; unified power flow controller; Control systems; Damping; Fuzzy neural networks; Hybrid power systems; Load flow; Power system control; Power system dynamics; Power system stability; Power system transients; Power systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Multi Topic Conference, 2003. INMIC 2003. 7th International

Print_ISBN

0-7803-8183-1

Type

conf

DOI

10.1109/INMIC.2003.1416727

Filename

1416727