Optimal placement of multiple STATCOM for voltage stability margin enhancement using particle swarm optimization

E. Nasr Azadani; S. H. Hosseinian; P. Hasanpor

doi:10.1007/s00202-008-0101-y

Optimal placement of multiple STATCOM for voltage stability margin enhancement using particle swarm optimization

E. Nasr Azadani, S. H. Hosseinian, P. Hasanpor

Not published at VTT

Research output: Contribution to journal › Article › Scientific › peer-review

35 Citations (Scopus)

Abstract

This paper proposes an approach for optimal placement of STATic synchronous COMpensator (STATCOM) in power systems. The approach is based on the simultaneous application of particle swarm optimization (PSO) and continuation power flow (CPF) to improve voltage profile, minimizing power system total losses, and for maximizing system loadability with respect to the size of STATCOM. Simulation results show the suitability of the PSO technique in finding multiple optimal solutions to the problem with reasonable computational effort. The installation of the STATOCM on these buses can increase the system voltage stability margin. The proposed technique is examined on the IEEE57 bus test system.

Original language	English
Pages (from-to)	503-510
Number of pages	8
Journal	Electrical Engineering
Volume	90
Issue number	7
DOIs	https://doi.org/10.1007/s00202-008-0101-y
Publication status	Published - 1 Sep 2008
MoE publication type	A1 Journal article-refereed

Keywords

Continuation power flow (CPF)
Loadability
Particle swarm optimization (PSO)
STATCOM

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10.1007/s00202-008-0101-y

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title = "Optimal placement of multiple STATCOM for voltage stability margin enhancement using particle swarm optimization",

abstract = "This paper proposes an approach for optimal placement of STATic synchronous COMpensator (STATCOM) in power systems. The approach is based on the simultaneous application of particle swarm optimization (PSO) and continuation power flow (CPF) to improve voltage profile, minimizing power system total losses, and for maximizing system loadability with respect to the size of STATCOM. Simulation results show the suitability of the PSO technique in finding multiple optimal solutions to the problem with reasonable computational effort. The installation of the STATOCM on these buses can increase the system voltage stability margin. The proposed technique is examined on the IEEE57 bus test system.",

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AU - Hosseinian, S. H.

AU - Hasanpor, P.

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Y1 - 2008/9/1

N2 - This paper proposes an approach for optimal placement of STATic synchronous COMpensator (STATCOM) in power systems. The approach is based on the simultaneous application of particle swarm optimization (PSO) and continuation power flow (CPF) to improve voltage profile, minimizing power system total losses, and for maximizing system loadability with respect to the size of STATCOM. Simulation results show the suitability of the PSO technique in finding multiple optimal solutions to the problem with reasonable computational effort. The installation of the STATOCM on these buses can increase the system voltage stability margin. The proposed technique is examined on the IEEE57 bus test system.

AB - This paper proposes an approach for optimal placement of STATic synchronous COMpensator (STATCOM) in power systems. The approach is based on the simultaneous application of particle swarm optimization (PSO) and continuation power flow (CPF) to improve voltage profile, minimizing power system total losses, and for maximizing system loadability with respect to the size of STATCOM. Simulation results show the suitability of the PSO technique in finding multiple optimal solutions to the problem with reasonable computational effort. The installation of the STATOCM on these buses can increase the system voltage stability margin. The proposed technique is examined on the IEEE57 bus test system.

KW - Continuation power flow (CPF)

KW - Loadability

KW - Particle swarm optimization (PSO)

KW - STATCOM

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JO - Electrical Engineering

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Optimal placement of multiple STATCOM for voltage stability margin enhancement using particle swarm optimization

Abstract

Keywords

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