Swarm Intelligence based Security Constrained Congestion Management using SSSC

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DC Field	Value	Language
dc.contributor.author	Kumar, D M Vinod	-
dc.contributor.author	Venkaiah, Ch	-
dc.date.accessioned	2024-11-26T05:01:03Z	-
dc.date.available	2024-11-26T05:01:03Z	-
dc.date.issued	2009	-
dc.identifier.citation	10.1109/APPEEC.2009.4918855	en_US
dc.identifier.uri	http://localhost:8080/xmlui/handle/123456789/1768	-
dc.description	NITW	en_US
dc.description.abstract	The power system is said to be in a state of congestion whenever the physical or operational constraints in a transmission network become active. In a deregulated environment, congestion in the transmission lines can be relieved by one of the two congestion management methodologies viz. cost free and non-cost free methods. In this paper, congestion is relieved by using cost free method and is reduced by employing static synchronous series compensator (SSSC). Genetic algorithm (GA) and particle swarm optimization (PSO) techniques were used to obtain the global optimal solution as the objective function is nonlinear in congestion management and these techniques were tested on IEEE 30-bus system.	en_US
dc.language.iso	en	en_US
dc.publisher	Asia-Pacific Power and Energy Engineering Conference, APPEEC	en_US
dc.subject	Congestion Management	en_US
dc.subject	Particle Swarm Optimization	en_US
dc.title	Swarm Intelligence based Security Constrained Congestion Management using SSSC	en_US
dc.type	Other	en_US
Appears in Collections:	Electrical Engineering

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