DocumentCode :
3210241
Title :
Differential evolution particle swarm optimization algorithm for reduction of network loss and voltage instability
Author :
Vaisakh, K. ; Sridhar, M. ; Linga Murthy, K.S.
Author_Institution :
Dept. of Electr. Eng., AU Coll. of Eng., Visakhapatnam, India
fYear :
2009
fDate :
9-11 Dec. 2009
Firstpage :
391
Lastpage :
396
Abstract :
This paper introduces a differential evolution particle swarm optimization (DEPSO) method for dealing with optimal reactive power dispatch aiming at power loss reduction and voltage stability improvement. The optimum reactive power dispatch of power systems is to allocate reactive power control variables so that the objective function composed of power losses is minimized and the prescribed voltage limits are satisfied. The proposed method determines the optimum settings of reactive power control variables such as, generator excitation, tap changing transformers, and shunt compensation that reduces the power loss, while maintaining the voltage stability. IEEE-30 bus test system from the literature is used to exemplify the performance of the proposed method. Numerical results show that the proposed method is better than the other methods reported in the literature.
Keywords :
compensation; evolutionary computation; optimal control; particle swarm optimisation; power generation dispatch; power system control; power transformers; reactive power control; voltage control; DEPSO method; IEEE-30 bus test system; differential evolution particle swarm optimization; generator excitation; network loss reduction; optimal reactive power dispatch; power loss reduction; power system; reactive power control; shunt compensation; tap changing transformer; voltage instability; voltage stability improvement; Particle swarm optimization; Power generation; Power system control; Power system stability; Power systems; Reactive power; Reactive power control; System testing; Transformers; Voltage; differential evolution; power loss reduction; reactive power dispatch; voltage stability L-index;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4244-5053-4
Type :
conf
DOI :
10.1109/NABIC.2009.5393308
Filename :
5393308
Link To Document :
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