DocumentCode :
3215268
Title :
Particle Swarm Optimization based corrective strategy to alleviate overloads in power system
Author :
Maharana, Manoj Kumar ; Swarup, K. Shanti
Author_Institution :
Dept. of Electr. Eng., Indian Inst. of Technol. Madras, Chennai, India
fYear :
2009
fDate :
9-11 Dec. 2009
Firstpage :
37
Lastpage :
42
Abstract :
This paper presents a new particle swarm optimization based corrective strategy to alleviate overloads of transmission lines. A direct acyclic graph (DAG) technique for selection of participating generators and buses with respect to a contingency is presented. Particle swarm optimization (PSO) technique has been employed for generator rescheduling and/or load shedding problem locally, to restore the system from abnormal to normal operating state. The effectiveness of the proposed approach is demonstrated for different contingency cases in IEEE 57 and modified IEEE 118 bus systems. The result shows that the proposed approach is computationally fast, reliable and efficient, in restoring the system to normal state after a contingency with minimal control actions.
Keywords :
IEEE standards; directed graphs; particle swarm optimisation; power generation control; power generation faults; system buses; transmission lines; IEEE 118 bus systems; IEEE 57; direct acyclic graph; generator rescheduling; load shedding problem; minimal control actions; particle swarm optimization; power system overloads; transmission lines; Control systems; Graph theory; Particle swarm optimization; Power generation; Power system control; Power system protection; Power system reliability; Power system security; Power systems; Power transmission lines; Corrective Strategy; Direct Acyclic Graph; Generator Rescheduling; Load Shedding; Particle Swarm Optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4244-5053-4
Type :
conf
DOI :
10.1109/NABIC.2009.5393597
Filename :
5393597
Link To Document :
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