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2009 Fifth International Conference on Natural Computation
A Self-Adaptive Improved Particle Swarm Optimization Algorithm and Its Application in Available Transfer Capability Calculation
Tianjian, China
August 14-August 16
ISBN: 978-0-7695-3736-8
ASCII Text
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Hou-he Chen, Guo-qing Li, Hai-liang Liao, "A Self-Adaptive Improved Particle Swarm Optimization Algorithm and Its Application in Available Transfer Capability Calculation," 2013 International Conference on Computing, Networking and Communications (ICNC), vol. 3, pp. 200-205, 2009 Fifth International Conference on Natural Computation, 2009.
 
 
BibTex
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@article{ 10.1109/ICNC.2009.214,
author = {Hou-he Chen and Guo-qing Li and Hai-liang Liao},
title = {A Self-Adaptive Improved Particle Swarm Optimization Algorithm and Its Application in Available Transfer Capability Calculation},
journal ={2013 International Conference on Computing, Networking and Communications (ICNC)},
volume = {3},
year = {2009},
isbn = {978-0-7695-3736-8},
pages = {200-205},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICNC.2009.214},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - 2013 International Conference on Computing, Networking and Communications (ICNC)
TI - A Self-Adaptive Improved Particle Swarm Optimization Algorithm and Its Application in Available Transfer Capability Calculation
SN - 978-0-7695-3736-8
SP200
EP205
A1 - Hou-he Chen,
A1 - Guo-qing Li,
A1 - Hai-liang Liao,
PY - 2009
VL - 3
JA - 2013 International Conference on Computing, Networking and Communications (ICNC)
ER -
 
A self-adaptive improved particle swarm optimization (IPSO) algorithm applied to available transfer capability (ATC) calculation is presented in this paper. Firstly, a new self-adaptive adjustment inertia-weighted strategy factor, which elevates the adaptability of particle swarm optimization (PSO) and accelerates convergence-speed of PSO, is proposed. Secondly, studying the search characteristics of PSO, penalty function is assigned dynamically. By this enhanced study behavior, the opportunity to find the global optimum is increased and the influence of the initial position of the particles is decreased. Thirdly, IPSO algorithm is adopted to solve the problem of ATC calculation. At last, the numeric simulation for IEEE 30-bus system demonstrates that this new IPSO is feasible and effective to solve the problem of ATC calculation.
Citation:
Hou-he Chen, Guo-qing Li, Hai-liang Liao, "A Self-Adaptive Improved Particle Swarm Optimization Algorithm and Its Application in Available Transfer Capability Calculation," icnc, vol. 3, pp.200-205, 2009 Fifth International Conference on Natural Computation, 2009
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