Predicting failures in power grids: The case of static overloads

Michael Chertkov, Feng Pan, Mikhail G. Stepanov

Research output: Contribution to journalArticle

49 Scopus citations

Abstract

Here we develop an approach to predict power grid weak points, and specifically to efficiently identify the most probable failure modes in static load distribution for a given power network. This approach is applied to two examples: Guam's power system and also the IEEE RTS-96 system, both modeled within the static dc power flow model. Our algorithm is a power network adaption of the worst configuration heuristics, originally developed to study low probability events in physics and failures in error-correction. One finding is that, if the normal operational mode of the grid is sufficiently healthy, the failure modes, also called instantons, are sufficiently sparse, i.e., the failures are caused by load fluctuations at only a few buses. The technique is useful for discovering weak links which are saturated at the instantons. It can also identify generators working at the capacity and generators under capacity, thus providing predictive capability for improving the reliability of any power network.

Original languageEnglish (US)
Article number5661887
Pages (from-to)150-160
Number of pages11
JournalIEEE Transactions on Smart Grid
Volume2
Issue number1
DOIs
StatePublished - Mar 1 2011
Externally publishedYes

Keywords

  • Distance to failure
  • power flow
  • rare events

ASJC Scopus subject areas

  • Computer Science(all)

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