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  • 标题:ATC Enhancement for Optimal Placement of FACTS using Artificial Intelligence (AI) Technique
  • 本地全文:下载
  • 作者:Manisha Agarwal ; Aziz Ahmed
  • 期刊名称:International Journal of Computer Science Issues
  • 印刷版ISSN:1694-0784
  • 电子版ISSN:1694-0814
  • 出版年度:2012
  • 卷号:9
  • 期号:3
  • 出版社:IJCSI Press
  • 摘要:The available transfer capability is one of the most important processes, used to identify the transfer of power between two areas without crossing the security constraints. To improve the available transfer capability between two areas, FACTS controllers are connected in the system. The major problem here is identifying the optimal location for fixing FACTS controller and the amount of voltage and angle to be injected in the system. By considering the aforementioned drawback, here a hybrid technique is proposed to identify the optimal location for fixing FACTS controller and the amount of voltage angle to be injected in the system. The hybrid technique includes neural network and genetic algorithm. Here, neural network is used to identify the optimal location for fixing FACTS controller in the system and genetic algorithm is used to determine the amount of voltage and angle to be injected in the system. By using this hybrid technique, the available transfer capability between the areas is improved as well as the power loss in the system is reduced. The result shows the performance of the proposed method in improving the ATC and reducing the total power losses in the system
  • 关键词:ATC; FACTS; SSSC; neural network; genetic algorithm
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