DocumentCode :
2540632
Title :
Optimal location and parameters setting of UPFC based on GA and PSO for enhancing power system security under single contingencies
Author :
Shaheen, H.I. ; Rashed, G.I. ; Cheng, S.J.
Author_Institution :
Coll. of Electr. & Electron. Eng., Huazhong Univ. of Sci. & Technol. (HUST), Wuhan
fYear :
2008
fDate :
20-24 July 2008
Firstpage :
1
Lastpage :
8
Abstract :
Unified power flow controller (UPFC) is one of the most effective flexible AC transmission systems (FACTS) devices for enhancing power system security. However, to what extent the performance of UPFC can be brought out, it highly depends upon the location and the parameters setting of this device in the system. This paper presents an approach to find out the optimal placement and the optimal parameters setting of UPFC for enhancing power system security under single contingencies (N-1 Contingency). Firstly, we perform a contingency analysis and ranking process to determine the severest line tripping contingencies considering line overloads and bus voltage violations as a performance index. Secondly, we apply genetic algorithm (GA) and particle swarm optimization (PSO) techniques to find out the optimal location and the optimal parameters setting of UPFC corresponding to the determined contingencies scenarios. To verify our proposed approach, we perform simulations on an IEEE 6-bus and an IEEE 14-bus power systems. The results wepsilave obtained indicate that GA and PSO can successfully achieve the proper settings and placement of UPFC. Installing UPFC in such location can significantly enhance the security of power system by eliminating or minimizing the overloaded lines and the bus voltage violations.
Keywords :
genetic algorithms; load flow control; particle swarm optimisation; power system security; FACTS devices; GA; IEEE 14-bus power systems; IEEE 6-bus power systems; PSO; UPFC; flexible AC transmission systems devices; genetic algorithm; line tripping contingencies; optimal location; overloaded lines; parameters setting; particle swarm optimization techniques; power system security; single contingencies; unified power flow controller; Flexible AC transmission systems; Genetic algorithms; Load flow; Particle swarm optimization; Power system analysis computing; Power system dynamics; Power system security; Power system simulation; Power system stability; Voltage control; Contingency Analysis; Genetic Algorithm (GA); Particle Swarm Optimization (PSO); Power Flow; Unified Power Flow Controller (UPFC);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, 2008 IEEE
Conference_Location :
Pittsburgh, PA
ISSN :
1932-5517
Print_ISBN :
978-1-4244-1905-0
Electronic_ISBN :
1932-5517
Type :
conf
DOI :
10.1109/PES.2008.4596594
Filename :
4596594
Link To Document :
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