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  • 标题:Fast Screening Method for an Important Transmission Line in Electrical Power System Uniting Internet Thinking and Physical Features
  • 本地全文:下载
  • 作者:Junqi Geng ; Xinghua Liu ; Xianming Sun
  • 期刊名称:Mobile Information Systems
  • 印刷版ISSN:1574-017X
  • 出版年度:2022
  • 卷号:2022
  • DOI:10.1155/2022/9670009
  • 语种:English
  • 出版社:Hindawi Publishing Corporation
  • 摘要:In the electrical power system, a few transmission lines may have cascading failures and even lead to severe blackout accidents. In order to further prevent the electrical power system from cascading failures and being enlightened by Internet thinking, based on the complex network theory, this paper proposes the TL-SALSA (transmission line-stochastic approach for link structure analysis) algorithm combining Internet thinking and physical characteristics of the electrical power system for screening the important transmission lines. The TL-SALSA algorithm not only retains the low-computational complexity advantage of the SALSA (stochastic approach for link structure analysis) algorithm but considers the impact relational among transmission lines and the electrical power system operation mode. The IEEE 39-bus power system and IEEE 118-bus power system are simulated and compared with the electric betweenness algorithm, and the results further evidence the effectiveness of the TL-SALSA algorithm. The results also show that the TL-SALSA algorithm can improve the screening efficiency by nearly three orders of magnitude compared with the electric betweenness algorithm, which proves the potential of the TL-SALSLA algorithm for screening important transmission lines in large-scale electrical power systems.
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