Maximizing transmission capacity through a minimum set of distributed multi-type FACTS

Author

Ghahremani, E. ; Kamwa, I.

Author_Institution

Dept. of Electr. & Comput. Eng., Laval Univ., Québec, QC, Canada

fYear

2012

fDate

22-26 July 2012

Firstpage

1

Lastpage

8

Abstract

The Flexible AC Transmission Systems (FACTS) devices can help the power system networks to reduce power flows on overloaded lines, resulting in increased system loadability, lower transmission line losses, improved power system stability and security, reduced power production costs, and more secure bus voltage levels. This paper presents a genetic algorithm (GA) based optimization process, for seeking optimal locations and parameters for multi-type FACTS devices in power systems. The optimization process is designed to maximize the power transmitted by the network. Five different FACTS devices are considered: SVC, TCSC, TCVR, TCPAR and UPFC. The simulation results show the effectiveness of the proposed optimization process in determining optimal placement of FACTS devices in several test networks.

Keywords

flexible AC transmission systems; genetic algorithms; power overhead lines; power system security; power system stability; GA based optimization process; SVC; TCPAR; TCSC; TCVR; UPFC; bus voltage levels; distributed multitype FACTS; flexible AC transmission systems devices; genetic algorithm; overloaded lines; power flows reduction; power production costs reduction; power system networks; power system security improvement; power system stability improvement; system loadability; test networks; transmission capacity maximization; transmission line losses; Genetic algorithms; Load flow; Power capacitors; Sociology; Static VAr compensators; Statistics; Thyristors; FACTS Devices; Maximum Loadability; Minimizing Transmission Line Losses; Optimal Placement; Power System Loadability;

fLanguage

English

Publisher

ieee

Conference_Titel

Power and Energy Society General Meeting, 2012 IEEE

Conference_Location

San Diego, CA

ISSN

1944-9925

Print_ISBN

978-1-4673-2727-5

Electronic_ISBN

1944-9925

Type

conf

DOI

10.1109/PESGM.2012.6343906

Filename

6343906