DocumentCode
1181897
Title
Optimal Power Flow by Enhanced Genetic Algorithm
Author
Bakirtzis, Anastasios G. ; Biskas, P. N. ; Zoumas, C. E. ; Petridis, V.
Author_Institution
Aristotle University, Greece
Volume
22
Issue
2
fYear
2002
Firstpage
60
Lastpage
60
Abstract
This paper presents an enhanced genetic algorithm for the solution of the optimal power flow with both continuous and discrete control variables. The continuous control variables modeled are unit active power outputs and generator-bus voltage magnitudes, while the discrete ones are transformer-tap settings and switchable shunt devices. A number of functional operating constraints, such as branch flow limits, load bus voltage magnitude limits, and generator reactive capabilities are included as penalties in the genetic algorithm fitness function. Advanced and problem-specific operators are introduced in order to enhance the algorithm´s efficiency and accuracy. Numerical results on two test systems are presented and compared with results of other approaches.
Keywords
Costs; Data analysis; Dictionaries; Genetic algorithms; Information analysis; Load flow; Power generation; Power system analysis computing; Power system dynamics; Protocols; Optimal power flow; genetic algorithms;
fLanguage
English
Journal_Title
Power Engineering Review, IEEE
Publisher
ieee
ISSN
0272-1724
Type
jour
DOI
10.1109/MPER.2002.4311997
Filename
4311997
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