DocumentCode :
3214845
Title :
Development of Ant Algorithm for load flow analysis
Author :
Kumar, Y. ; Dwivedi, K. ; Agnihotri, Ganga
fYear :
2009
fDate :
15-18 March 2009
Firstpage :
1
Lastpage :
5
Abstract :
Basic ant colony algorithm is one kind of new heuristic biological modeling method which has the ability of global searching. In this paper, an efficient and reliable ant algorithm based load flow algorithm is developed. The load flow equations of a power system containing FACTS will be much more nonlinear and the equation set may be non-convex. The conventional NRLF method may not solve these equations satisfactorily. The load flow problem is solved as optimization problem in the proposed method. The developed method, do not fail even with non-linear and heavy load due to virtue of ant algorithm. The different constraints, voltage, current and overloading are also considered. The power balance requirement and voltage magnitude constraint satisfaction methods in the algorithm are presented and incorporated into the ant algorithm for solving load flow problem. The new algorithm can determine multiple load flow solutions and can be used to determine multiple load flow solutions and to determine the loadability limits of transmission system. The developed method is tested on different test systems and found accurate, efficient and successful with non-linear load also.
Keywords :
flexible AC transmission systems; load flow; optimisation; FACTS; ant colony algorithm; flexible AC transmission systems; heuristic biological modeling method; load flow analysis; optimization problem; power balance requirement; power system; transmission system; voltage magnitude constraint satisfaction method; Biological system modeling; Load flow; Load flow analysis; Nonlinear equations; Optimization methods; Power system analysis computing; Power system modeling; Power system reliability; System testing; Voltage; Ant; Genetic algorithm; load flow;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Systems Conference and Exposition, 2009. PSCE '09. IEEE/PES
Conference_Location :
Seattle, WA
Print_ISBN :
978-1-4244-3810-5
Electronic_ISBN :
978-1-4244-3811-2
Type :
conf
DOI :
10.1109/PSCE.2009.4840002
Filename :
4840002
Link To Document :
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