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Research Article

Comparative Analysis of GA and PSO Optimization for Power System Stability Parameters

Atul M. Gajare  ·  Dr. R. P. Singh

IJDACR Vol.5 No.11 (June 2017) ISSN 2319-4863 Open Access Peer Reviewed

Journal

International Journal of Digital Applications and Contemporary Research (IJDACR)

ISSN

2319-4863

Volume / Issue

Vol.5 · Issue 11

Published

June 2017

Access

Open Access

Licence

CC BY-NC-SA 4.0

Authors

Atul M. Gajare Dr. R. P. Singh

Abstract

The designing of power transmission network is a difficult task due to the complexity of power system. Due to the complexity of the power system, there is always a loss of the stability due to the fault. Whenever a fault is intercepted in the system, the whole system goes to severe transients. These transients cause oscillation in phase angle which leads poor power quality. The nature of oscillation is increasing instead of being sustained, which leads system failure in form of generator damage. To reduce and eliminate the unstable oscillations one needs to use a stabilizer which can generate a perfect compensatory signal in order to minimize the harmonics generated due to instability. This paper presents a Power System stabilizer to reduce oscillations due to small signal disturbance. We also applied Genetic algorithm (GA) and Particle swarm optimization (PSO) for the parameter tuning of the stabilizer. The reason behind the use of GA and PSO instead of conventional methods is that it searches the parameter heuristically, which leads better results. The effectiveness of proposed stabilizers for suppressing oscillation due to change in mechanical input and excitation is examined by investigating their change in rotor angle and power angle deviation in the SMIB system.

How to Cite

Atul M. Gajare, Dr. R. P. Singh (2017). Comparative Analysis of GA and PSO Optimization for Power System Stability Parameters. International Journal of Digital Applications and Contemporary Research (IJDACR), Vol.5, Issue 11. ISSN: 2319-4863.

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Article Info

Journal IJDACR
Volume Vol. 5
Issue No. 11
Month June
Year 2017
ISSN 2319-4863
Access Open Access

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