首页    期刊浏览 2024年11月08日 星期五
登录注册

文章基本信息

  • 标题:Optimal SVC allocation via symbiotic organisms search for voltage security improvement
  • 本地全文:下载
  • 作者:Mohamad Khairuzzaman Mohamad Zamani ; Ismail Musirin ; Sharifah Azma Syed Mustaffa
  • 期刊名称:TELKOMNIKA (Telecommunication Computing Electronics and Control)
  • 印刷版ISSN:2302-9293
  • 出版年度:2019
  • 卷号:17
  • 期号:3
  • 页码:1267-1274
  • DOI:10.12928/telkomnika.v17i3.9905
  • 出版社:Universitas Ahmad Dahlan
  • 摘要:It is desirable that a power system operation is in a normal operating condition. However, the increase of load demand in a power system has forced the system to operate near to its stability limit whereby an increase in load poses a threat to the power system security. In solving this issue, optimal reactive power support via SVC allocation in a power system has been proposed. In this paper, Symbiotic Organisms Search (SOS) algorithm is implemented to solve for optimal allocation of SVC in the power system. IEEE 26 Bus Reliability Test System is used as the test system. Comparative studies are also conducted concerning Particle Swarm Optimization (PSO) and Evolutionary Programming (EP) techniques based on several case studies. Based on the result, SOS has proven its superiority by producing higher quality solutions compared to PSO and EP. The results of this study can benefit the power system operators in planning for optimal power system operations.
  • 其他摘要:It is desirable that a power system operation is in a normal operating condition. However, the increase of load demand in a power system has forced the system to operate near to its stability limit whereby an increase in load poses a threat to the power system security. In solving this issue, optimal reactive power support via SVC allocation in a power system has been proposed. In this paper, Symbiotic Organisms Search (SOS) algorithm is implemented to solve for optimal allocation of SVC in the power system. IEEE 26 Bus Reliability Test System is used as the test system. Comparative studies are also conducted concerning Particle Swarm Optimization (PSO) and Evolutionary Programming (EP) techniques based on several case studies. Based on the result, SOS has proven its superiority by producing higher quality solutions compared to PSO and EP. The results of this study can benefit the power system operators in planning for optimal power system operations.
  • 关键词:fast voltage stability index;static var compensator;symbiotic organisms search;voltage deviation index
国家哲学社会科学文献中心版权所有