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Coordination Tuning PID-PSS and TCSC Based Model of Single Machine Infinite-Bus Using Combination Bacteria Foraging-Particle Swam Optimization Method

Ida Bagus Gede Manuaba(1*), Ardyono Priyadi(2), Mauridhi Hery P.(3)

(1) Department of Electrical Engineering, Sepuluh Nopember Institute of Technology Department of Electrical Engineering, Udayana University, Indonesia
(2) Department of Electrical Engineering, Sepuluh Nopember Institute of Technology, Indonesia
(3) Department of Electrical Engineering, Sepuluh Nopember Institute of Technology, Indonesia
(*) Corresponding author



The power system requires optimal tuning of automatic voltage regulator (AVR) controller and power system stabilizer (PSS) parameters to get a satisfactory operation. With the increase of transmission line loading over long distances, the use of PSS in some cases may not provide sufficient damping. Application method to get the optimal parameter tuning individual controller causes the AVR to improve voltage regulation and PSS to increase the damping of the system. Simultaneous tuning of AVR, PSS and flexible ac transmission systems (FACTS) damping controller is needed to guarantee a kind closed loop system outcome and to obtain a better voltage regulation and oscillation damping in the system. This paper presents coordination tuning power system stabilizer and a thyristor controlled series compensator (TCSC) using evolutionary computation. The problem of obtaining the optimal controller parameters was formulated as an optimization problem and bacteria foraging-particle swarm optimization with time varying acceleration-differential evolution algorithm applied to solve the optimization problem. The parameters such as proportional gain, integral factor, differential coefficient were selected and optimized by bacteria foraging-particle swarm optimization with time varying acceleration-differential evolution algorithm (BFOPSOTVACDE). The suggested methods applied to tuning PSS and TCSC are compared to another method, as shown in the result. Performance index of systems obtained using suggested method was 0.9053.
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Power System Dynamics; Flexible AC Transmission Systems; Evolutionary Computation; Power System Stability

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