DocumentCode :
1507849
Title :
Optimal location of multi-type FACTS devices in a power system by means of genetic algorithms
Author :
Gerbex, Stéphane ; Cherkaoui, Rachid ; Germond, Alain J.
Author_Institution :
Lab. de Reseaux d´´Energie Electr., Ecole Polytech. Federale de Lausanne, Switzerland
Volume :
16
Issue :
3
fYear :
2001
fDate :
8/1/2001 12:00:00 AM
Firstpage :
537
Lastpage :
544
Abstract :
This paper presents a genetic algorithm to seek the optimal location of multi-type FACTS devices in a power system. The optimizations are performed on three parameters: the location of the devices, their types and their values. The system loadability is applied as a measure of power system performance. Four different kinds of FACTS controllers are used and modeled for steady-state studies: TCSC, TCPST, TCVR and SVC. Simulations are done on a 118-bus power system for several numbers of devices. Results show the difference of efficiency of the devices used in this context. They also show that the simultaneous use of several kinds of controllers is the most efficient solution to increase the loadability of the system. In all the cases (single- and multi-type FACTS devices), we observe a maximum number of devices beyond which this loadability cannot be improved
Keywords :
flexible AC transmission systems; genetic algorithms; power systems; 118-bus power system; FACTS controllers; SVC; TCSC; device efficiency; genetic algorithms; loadability; multi-type FACTS devices; optimal location; power system; single-type FACTS devices; static VAr compensator; system loadability; thyristor controlled phase shifting transformer; thyristor controlled series capacitor; thyristor controlled voltage regulator; Genetic algorithms; Power capacitors; Power measurement; Power system measurements; Power system modeling; Power system simulation; Power systems; Static VAr compensators; Steady-state; Thyristors;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/59.932292
Filename :
932292
Link To Document :
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