Computing Criticality of Lines in Power Systems

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We propose a computationally efficient method based onnonlinear optimization to identify critical lines, failure of which cancause severe blackouts. Our method computes criticality measure for alllines at a time, as opposed to detecting a single vulnerability,providing a global view of the system. This information on criticality oflines can be used to identify multiple contingencies by selectivelyexploring multiple combinations of broken lines. The effectiveness of ourmethod is demonstrated on the IEEE 30 and 118 bus systems, where we canvery quickly detect the most critical lines in the system and identifysevere multiple contingencies.

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Pinar, Ali; Reichert, Adam & Lesieutre, Bernard October 13, 2006.

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We propose a computationally efficient method based onnonlinear optimization to identify critical lines, failure of which cancause severe blackouts. Our method computes criticality measure for alllines at a time, as opposed to detecting a single vulnerability,providing a global view of the system. This information on criticality oflines can be used to identify multiple contingencies by selectivelyexploring multiple combinations of broken lines. The effectiveness of ourmethod is demonstrated on the IEEE 30 and 118 bus systems, where we canvery quickly detect the most critical lines in the system and identifysevere multiple contingencies.

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  • 2007 IEEE International Symposium on Circuits andSystems, New Orleans, LA, 27-30 May,2007

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  • Report No.: LBNL--61763
  • Grant Number: DE-AC02-05CH11231
  • Office of Scientific & Technical Information Report Number: 918487
  • Archival Resource Key: ark:/67531/metadc883764

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  • October 13, 2006

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  • Sept. 22, 2016, 2:13 a.m.

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  • Sept. 30, 2016, 1:04 p.m.

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Pinar, Ali; Reichert, Adam & Lesieutre, Bernard. Computing Criticality of Lines in Power Systems, article, October 13, 2006; Berkeley, California. (digital.library.unt.edu/ark:/67531/metadc883764/: accessed August 20, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.