DocumentCode
3273006
Title
Optimal power flow using group search optimizer with intraspecific competition and lévy walk
Author
Li, Y.Z. ; Li, M.S. ; Ji, Zhen ; Wu, Q.H.
Author_Institution
Sch. of Electr. Eng., South China Univ. of Technol. (SCUT), Guangzhou, China
fYear
2013
fDate
16-19 April 2013
Firstpage
256
Lastpage
262
Abstract
This paper presents an enhanced group search optimizer (GSO), group search optimizer with intraspecific competition and lévy walk (GSOICLW), to solve the optimal power flow (OPF) problem. GSOICLW s a more biologically realistic algorithm and performs better balance between global and local searching than GSO n hat intraspecific competition IC) and lévy walk (LW) are introduced o GSO. GSOICLW is tested or the OPF problem on the IEEE 30-bus power system, with green house gases emission constraint considered. Simulation results demonstrate the accuracy and reliability of the proposed algorithm, compared with other evolutionary algorithms EAs).
Keywords
air pollution; evolutionary computation; optimisation; power system analysis computing; GSOICLW; IEEE 30-bus power system; Lévy walk; OPF; evolutionary algorithms; green house gases emission constraint; group search optimizer; intraspecific competition; optimal power flow; EPON; IEEE 802.3 Standards; Optimal power flow; evolutionary algorithms; group search optimizer intraspecific competition; lévy walk;
fLanguage
English
Publisher
ieee
Conference_Titel
Swarm Intelligence (SIS), 2013 IEEE Symposium on
Conference_Location
Singapore
Type
conf
DOI
10.1109/SIS.2013.6615187
Filename
6615187
Link To Document