Swarm and bacterial foraging based optimal power system stabilizer for stability improvement

2016 ◽  
Author(s):  
Prakash K. Ray ◽  
Shiba R. Paital ◽  
Asit Mohanty ◽  
T. K. Panigrahi ◽  
Manish Kumar ◽  
...  
Keyword(s):  
Power System ◽  
Power System Stabilizer ◽  
Bacterial Foraging ◽  
Optimal Power ◽  
System Stabilizer

scholarly journals Design of Optimal Power System Stabilizer Using ETAP

2012 ◽  
pp. 221-224
Author(s):  
Raja Nivedha. R ◽  
Sreevidya. L ◽  
V. Geetha ◽  
R. Deepa
Keyword(s):  
Power System ◽  
Optimal Power Flow ◽  
Transient Stability ◽  
Transient Behavior ◽  
Steel Plant ◽  
Power System Stabilizer ◽  
Optimal Power ◽  
Clearing Time ◽  
System Stabilizer ◽  
System Power

The main objective of this paper is to improve the critical clearing time of the Steel Plant 35 MW Turbo generator. In order to enhance the transient behavior of the system, Power System Stabilizer is added so that proper damping is done. Damping intra area and inter area oscillations are critical to optimal power flow and stability on a system. Power system stabilizer is an effective damping device, as they provide auxiliary control signals to the excitation system of the generator. Transient stability analysis was carried out for the Steel plant. The three phase to ground and line to ground fault was simulated. The critical clearing time was found to be more when Power System Stabilizer was added and when Power System Stabilizer was not added the critical clearing time has considerably reduced.

Robust design of power system stabilizer using bacterial foraging algorithm

2013 ◽  
Vol 62 (1) ◽  
pp. 141-152 ◽  
Author(s):  
K. Abdul Hameed ◽  
S. Palani
Keyword(s):  
Power System ◽  
Low Frequency ◽  
Operating Conditions ◽  
Power System Stabilizer ◽  
Bacterial Foraging ◽  
Wide Range ◽  
Bacterial Foraging Algorithm ◽  
Simulation Results ◽  
The Time Domain ◽  
System Stabilizer

Abstract In this paper, a novel bacterial foraging algorithm (BFA) based approach for robust and optimal design of PID controller connected to power system stabilizer (PSS) is proposed for damping low frequency power oscillations of a single machine infinite bus bar (SMIB) power system. This paper attempts to optimize three parameters (Kp, Ki, Kd) of PID-PSS based on foraging behaviour of Escherichia coli bacteria in human intestine. The problem of robustly selecting the parameters of the power system stabilizer is converted to an optimization problem which is solved by a bacterial foraging algorithm with a carefully selected objective function. The eigenvalue analysis and the simulation results obtained for internal and external disturbances for a wide range of operating conditions show the effectiveness and robustness of the proposed BFAPSS. Further, the time domain simulation results when compared with those obtained using conventional PSS and Genetic Algorithm (GA) based PSS show the superiority of the proposed design.

scholarly journals DESAIN OPTIMAL POWER SISTEM STABILIZER PADA UNIT PEMBANGKIT BAKARU BERBASIS ANT COLONY OPTIMIZATION

Transmisi ◽  
2019 ◽  
Vol 21 (3) ◽  
pp. 70
Author(s):  
Muhammad Ruswandi Djalal ◽  
Herman Nawir ◽  
Sonong Sonong ◽  
Marhatang Marhatang
Keyword(s):  
Power System ◽  
Ant Colony Optimization ◽  
Ant Colony ◽  
Power System Stabilizer ◽  
Optimal Power ◽  
System Stabilizer

Salah satu peralatan kontrol tambahan yang mampu meningkatkan kestabilan suatu system pada generator adalah Power System Stabilizer (PSS). Ketika terjadi osilasi gangguan pada generator, PSS memberikan sinyal tambahan ke peralatan eksitasi untuk memberikan redaman tambahan pada generator. Penggunaan PSS diperlukan koordinasi penentuan parameter yang tepat untuk mencapai kontrol kinerja yang bagus untuk sistem. Pada penelitian ini, metode kecerdasan buatan algoritma Ant Colony Optimization (ACO) digunakan untuk mengoptimasi parameter PSS. Dari hasil simulasi didapatkan parameter PSS yang optimal ditinjau dari respon osilasi overshoot dan sudut rotor. Kinerja sistem tanpa PSS didapatkan overshoot frekuensi sebesar -0,02242 s/d 0,005241 pu, kemudian PSS dengan Trial error sebesar -0,0196 s/d 0,003704 pu, PSS Bat sebesar -0.01394 s/d 0.0007533 pu, dan dengan metode ant colony didapatkan overshoot yang berkurang yaitu sebesar -0,0128 s/d 0,0003349 pu. Sedangkan untuk respon sudut rotor didapatkan tanpa PSS sebesar -4,71 s/d 4,486e-05 pu, PSS trial error sebesar -4,579 s/d 4,486e-05 pu, PSS Bat sebesar -4.71 s/d 4.486e-05, dan PSS ant colony sebesar -4,566 s/d 4,545e-05 pu. Implementasi metode cerdas sebagai metode penalaan PSS dapat memperbaiki kinerja generator dalam meredam osilasi sistem multimesin.

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