Comparison of Different Techniques For Tuning of Power System Stabilizer

Ehsan BAYAT, Hadi DELAVARİ
1.987 740

Abstract


Abstract. The power system is subjected to different types of disturbances such as small changes in the load that affects its efficiency and sometimes leads to unstable system. These disturbances cause oscillations at low frequencies that are undesirable since it affects the amount of transferred power through the transmission lines and leads to external stress to the mechanical shaft. In order to compress low-frequency oscillations, a common solution is use the power system stabilizer (PSS). In this paper different techniques for Tuning of power system stabilizer is proposed. The parameters of the power system stabilizer has been tuned by the three ways, particle swarm optimization (PSO), genetic algorithm (GA) and teaching–learning based optimization (TLBO). The simulation results indicate the performance of the teaching learning based power system stabilizer is much better than the particle swarm optimization power system stabilizer and genetic algorithm based power system stabilizer.


Keywords


Power System Stabilizer, Teaching–Learning Based Optimization, Particle Swarm Optimization, Genetic Algorithm

Full Text:

PDF


References


Nasar. A, P. J. (2013). Performance Evaluation ofGA and RL based PSS of a Multi-Machine

System. International Conference on Circuits, Power and Computing Technologies, 461- 4

Lin, Y.-J. (2013). Proportional plus derivative output feedback based fuzzy logic power system stabiliser. Electrical Power and Energy Systems, 301-307.

Bhati, R. G. (2013). Robust fuzzy logic power system stabilizer based on evolution and learning. Electrical Power and Energy Systems, 357-366. 5 4 5 5