DocumentCode :
160310
Title :
Evolutionary algorithm-based technique for power system security enhancement
Author :
Rambabu, Chunduri ; Obulesu, Y.P. ; Saibabu, C.
Author_Institution :
EEE Dept., Sri Vasavi Eng. Coll., Tadepalligudem, India
fYear :
2014
fDate :
9-11 Jan. 2014
Firstpage :
1
Lastpage :
5
Abstract :
Security constraint optimal power flow is one of the most cost effective measures to promote both cost minimization and maximum voltage security without jeopardizing the system operation. It is developed into a multi-objective problem that involves objectives such as economical operating condition of the system and system security margin. This paper explores the application of Particle Swarm Optimization Algorithm (PSO) to solve the security enhancement problem. In this paper, a novel fuzzy logic composite multi-objective evolutionary algorithm for security problem is presented. Flexible AC Transmission Systems (FACTS) devices, are modern compensators of active and reactive powers, can be considered viable options in providing security enhancement. The proposed algorithm is tested on the IEEE 30-bus system. The proposed methods have achieved solutions with good accuracy, stable convergence characteristics, simple implementation and satisfactory computation time.
Keywords :
flexible AC transmission systems; fuzzy logic; particle swarm optimisation; power system security; FACTS; IEEE 30-bus system; cost minimization; economical operating condition; flexible AC transmission systems; fuzzy logic; maximum voltage security; multiobjective evolutionary algorithm; multiobjective problem; optimal power flow; particle swarm optimization algorithm; power system security enhancement; security enhancement problem; Indexes; Power capacitors; Power system stability; Reactive power; Security; Silicon; Thyristors; Fuzzy Logic; Particle Swarm Optimization; Power System Security; TCSC;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Electrical Engineering (ICAEE), 2014 International Conference on
Conference_Location :
Vellore
Type :
conf
DOI :
10.1109/ICAEE.2014.6838521
Filename :
6838521
Link To Document :
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