DocumentCode
2915073
Title
Optimal Power Flow Based on Modified Genetic Algorithm
Author
Moasheri, Seyed Reza ; Khazraei, Masoud
Author_Institution
Islamic Azad Univ., Gonabad, Iran
fYear
2011
fDate
25-28 March 2011
Firstpage
1
Lastpage
5
Abstract
Cost minimization is one of the main goals in electric market so economic dispatch and load allocating, named as optimal power flow (OPF), are more interesting concerns. In this paper a Modified Genetic Algorithm (MGA) is presented for the solution of the OPF. The control variables are unit active power outputs, generator-bus voltages and discrete transformer-tap settings. To overcome the operating constraints such as line flow limits, generator capabilities, and bus voltage amplitude limits, are all included in MGA fitness function. The simulation results have shown the MGA is more efficient and more convergence in compare with other attempts.
Keywords
genetic algorithms; load flow; power systems; power transformers; MGA fitness function; control variables; cost minimization; discrete transformer-tap settings; electric market; generator-bus voltages; modified genetic algorithm; optimal power flow; power system; Fuels; Gallium; Generators; Genetic algorithms; Load flow; Optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Power and Energy Engineering Conference (APPEEC), 2011 Asia-Pacific
Conference_Location
Wuhan
ISSN
2157-4839
Print_ISBN
978-1-4244-6253-7
Type
conf
DOI
10.1109/APPEEC.2011.5747746
Filename
5747746
Link To Document