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  • 标题:OPTIMAL SETTING GAIN OF PSS-AVR BASED ON PARTICLE SWARM OPTIMIZATION FOR POWER SYSTEM STABILITY IMPROVEMENT
  • 本地全文:下载
  • 作者:MUHAMAD HADDIN ; SOEBAGIO ; ADI SOEPRIJANTO
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2012
  • 卷号:42
  • 期号:1
  • 页码:042-048
  • 出版社:Journal of Theoretical and Applied
  • 摘要:This paper presents the settings of automatic voltage regulator (AVR) and power system stabilizer (PSS) on a single machine infinite bus (SMIB) to improve the dynamic stability of the power system. This setting is done by determining the fitness function of AVR (KA) and PSS (KPSS) gain using Particle Swarm Optimization (PSO) algorithm. The main purpose of this setting is to minimize the oscillation frequency so that it would improve the stability of electric power. Simulations are conducted by inputting step function with 5% load fluctuations as a representation of dynamic load. Simulation results show that the proposed method is very effective for improving the damping of electromechanical oscillations of the power system. The proposed method shows that the power system produces a reduced rate of 11% overshoot and settling time 40%.
  • 关键词:Setting Gain of PSS-AVR; Dynamic Stability; Modified PSO
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