REDUCING CLUSTER SIZE FOR COMPUTING REMEDIAL ADJUSTMENTS FOR VOLTAGE AND LOADING VIOLATIONS ON THE POWER SYSTEM.

S. Y. Lin, Garng Morton Huang, John Zaborszky

Research output: Contribution to journalConference article

1 Citation (Scopus)

Abstract

A technique was earlier proposed by the authors (1983, 1984) for solving sectional outbreaks of voltage and overload violations on large electric power transmission systems by finding relatively small size clusters of controls and violated, as well as nonviolated, network elements to which they react sensitively. Because the clusters are as much as two orders of magnitude smaller than the entire system, immense savings of computation are possible. Unfortunately, the size of the clusters cannot be well regulated a priori, so there is a possibility for oversize clusters. An effective algorithm is introduced for splitting up such undesirably large clusters by inactivating a few well-chosen controls. It was necessary to use some new results in graph theory to develop the new algorithm.

Original languageEnglish
Pages (from-to)467-475
Number of pages9
JournalProceedings of the IEEE Conference on Decision and Control
Publication statusPublished - 1 Dec 1984
Externally publishedYes

Fingerprint

Power System
Adjustment
Voltage
Electric power transmission
Computing
Graph theory
Electric potential
Overload
Entire
Necessary

ASJC Scopus subject areas

  • Chemical Health and Safety
  • Control and Systems Engineering
  • Safety, Risk, Reliability and Quality

Cite this

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title = "REDUCING CLUSTER SIZE FOR COMPUTING REMEDIAL ADJUSTMENTS FOR VOLTAGE AND LOADING VIOLATIONS ON THE POWER SYSTEM.",
abstract = "A technique was earlier proposed by the authors (1983, 1984) for solving sectional outbreaks of voltage and overload violations on large electric power transmission systems by finding relatively small size clusters of controls and violated, as well as nonviolated, network elements to which they react sensitively. Because the clusters are as much as two orders of magnitude smaller than the entire system, immense savings of computation are possible. Unfortunately, the size of the clusters cannot be well regulated a priori, so there is a possibility for oversize clusters. An effective algorithm is introduced for splitting up such undesirably large clusters by inactivating a few well-chosen controls. It was necessary to use some new results in graph theory to develop the new algorithm.",
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AU - Huang, Garng Morton

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