DocumentCode :
2635085
Title :
A new multi-objective optimization technique for generation dispatch
Author :
Karakas, Arif ; Kocatepe, Celal ; Li, Fangxing
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of Tennessee, Knoxville, TN, USA
fYear :
2009
fDate :
4-6 Oct. 2009
Firstpage :
1
Lastpage :
6
Abstract :
The economic and secure operation of power systems has significant importance. Due to technical limitations, the best economical operation point is not always the desired operating point for the system stability. In this study, first, the most economical operating point is obtained by solving the non-linear, network-constrained economic dispatch problem using genetic algorithm. Then, the system voltage stability is taken into account to compare the different possible operating points using V-Q sensitivity analysis. Finally, these two criteria are combined using the learning automata technique to achieve a multi-objective optimization solution, which corresponds to a desired operating point considering both economical operation and stability region. This is of particular interest in regions with significant concerns of voltage stability. The methodology was implemented in MATLAB and applied on a 6-bus test system. The same technique of learning automata may be applied in the future to similar problems that need multi-objective consideration.
Keywords :
Genetic algorithms; Learning automata; MATLAB; Power generation economics; Power system economics; Power system stability; Sensitivity analysis; Stability analysis; Stability criteria; Voltage; Economic dispatch; genetic algorithm; learning automata; voltage stability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
North American Power Symposium (NAPS), 2009
Conference_Location :
Starkville, MS, USA
Print_ISBN :
978-1-4244-4428-1
Electronic_ISBN :
978-1-4244-4429-8
Type :
conf
DOI :
10.1109/NAPS.2009.5484049
Filename :
5484049
Link To Document :
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