DocumentCode
3394769
Title
Skeleton-Network Reconfiguration Based on Node Importance and Line Optimization
Author
Huang, Jin-kai ; Du, Liang ; Zhang, Guo-song
Author_Institution
Sichuan Electr. Vocational & Tech. Coll., Chengdu, China
fYear
2012
fDate
27-29 March 2012
Firstpage
1
Lastpage
4
Abstract
In power system restoration process, power transmission network reconstruction problem is studied. Using a complex network related theory, putting forward a comprehensive consideration node importance and transmission lines optimization network reconfiguration method. This method considers the influence of shunt capacitance on node importance, realizes the weighted power transmission network reconfiguration, the index make both important node and Line Optimization realize, achieveing the whole optimization of the reconstruction network. The genetic algorithm method with characteristics of global optimization and handling the discrete variables easily and effectively is employed to solve this problem. Finally, IEEE39 test system is applied as benchmark to demonstrate the effectiveness and validity of the proposed method.
Keywords
IEEE standards; genetic algorithms; power system restoration; power transmission lines; IEEE39 test system; complex network related theory; comprehensive consideration node importance; discrete variables; genetic algorithm method; global optimization characteristics; node importance; power system restoration process; power transmission network reconstruction problem; shunt capacitance; skeleton-network reconfiguration; transmission line optimization network reconfiguration method; weighted power transmission network reconfiguration; Algorithm design and analysis; Complex networks; Educational institutions; Genetic algorithms; Optimization; Reactive power;
fLanguage
English
Publisher
ieee
Conference_Titel
Power and Energy Engineering Conference (APPEEC), 2012 Asia-Pacific
Conference_Location
Shanghai
ISSN
2157-4839
Print_ISBN
978-1-4577-0545-8
Type
conf
DOI
10.1109/APPEEC.2012.6307449
Filename
6307449
Link To Document