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Title: Particle swarm optimization based defensive islanding of large scale power system
Author (s): Wenxin Liu
Cartes, D.A.
Venayagamoorthy, Ganesh K.
Department/Lab Affiliations: Electrical and Computer Engineering
Real-Time Power and Intelligent Systems Laboratory
Keywords: Islanding operating
and system splitting
particle swarm optimization
splitting strategies
Issue Date: 2006
Publisher: Institute of Electrical and Electronics Engineers
Citation: Wenxin Liu; Cartes, D.A.; Venayagamoorthy, G.K. "Particle Swarm Optimization based Defensive Islanding of Large Scale Power System" IJCNN '06. International Joint Conference on Neural Networks, 2006. 16-21 July 2006 Pages: 1719- 1725
Abstract: Defensive islanding is an efficient way to avoid catastrophic failures and wide area blackouts. Power system splitting especially for large scale power systems is a combinatorial explosion problem. Thus, it is very difficult to find an optimal solution (if one exists) for large scale power system in real time. This paper proposes to utilize the computational efficiency property of Binary Particle Swarm Optimization (BPSO) to find some efficient splitting solutions in limited timeframe. The solutions are optimized based on a cost function considering the balance between real power generation and consumption, the relative importance of customers, the capacities of distribution and transmission systems, and possibility of region to be impacted, etc. The solutions not only provide the lines to cut but also the corresponding load shedding information in each island. Simulations with large scale power system demonstrate the effectiveness of the proposed algorithm.
Type: Article - Conference proceedings
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titleParticle swarm optimization based defensive islanding of large scale power system
contributor.authorWenxin Liu
contributor.authorCartes, D.A.
contributor.authorVenayagamoorthy, Ganesh K.
contributor.deptlabElectrical and Computer Engineering
contributor.deptlabReal-Time Power and Intelligent Systems Laboratory
subjectIslanding operating
subjectand system splitting
subjectparticle swarm optimization
subjectsplitting strategies
date.issued2006
date.submitted2007
publisherInstitute of Electrical and Electronics Engineers
identifier.citationWenxin Liu; Cartes, D.A.; Venayagamoorthy, G.K. "Particle Swarm Optimization based Defensive Islanding of Large Scale Power System" IJCNN '06. International Joint Conference on Neural Networks, 2006. 16-21 July 2006 Pages: 1719- 1725
identifier.pub.URI
http://ieeexplore.ieee.org/iel5/11216/36115/01716315.pdf?arnumber=171631
description.abstractDefensive islanding is an efficient way to avoid catastrophic failures and wide area blackouts. Power system splitting especially for large scale power systems is a combinatorial explosion problem. Thus, it is very difficult to find an optimal solution (if one exists) for large scale power system in real time. This paper proposes to utilize the computational efficiency property of Binary Particle Swarm Optimization (BPSO) to find some efficient splitting solutions in limited timeframe. The solutions are optimized based on a cost function considering the balance between real power generation and consumption, the relative importance of customers, the capacities of distribution and transmission systems, and possibility of region to be impacted, etc. The solutions not only provide the lines to cut but also the corresponding load shedding information in each island. Simulations with large scale power system demonstrate the effectiveness of the proposed algorithm.
typeArticle - Conference proceedings
type.DCMITypetext
type.statusFinal version
rightsThis material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
rights.URI
http://www.ieee.org/web/publications/rights/policies.html
date.accessioned2007-04-05T14:28:12Z
date.available2007-04-05T14:28:11Z
identifier.persist.URI
http://scholarsmine.mst.edu/post_prints/01716315_09007dcc8030db72.html
Full Text
01716315_09007dcc8030db77.pdf