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IEEE Transactions on Power Systems
Article . 1996 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Comparison of algorithms for transient stability simulations on shared and distributed memory multiprocessors

Authors: M. La Scala; G. Sblendorio; A. Bose; J. Q. Wu;

Comparison of algorithms for transient stability simulations on shared and distributed memory multiprocessors

Abstract

Parallel processing has been applied for time domain simulations of power system transient behavior in order to implement real-time dynamic security assessment. In this paper, two different algorithms have been implemented and compared: the Shifted-Picard (SP) and the Very DisHonest Newton (VDHN). The former has been proved to be effective when parallelism-in-time is adopted whereas the latter is an effective solver when parallelism-in-space is exploited. Furthermore, two different parallel computing architectures have been considered: namely, the Sequent Symmetry computer with 26 processors which is a data shared memory machine and the nCUBE characterized by 128 CPUs which is a typical message passing parallel machine. A realistic network with 662 buses has been used to assess the performance of the different implementations. The comparison of the results allows the reader to understand both the limitations of the algorithmic approaches and the constraints imposed by the two parallel architectures. An optimal grain of the parallelism associated to the problem can be identified through the reported experience.

Country
Italy
Keywords

Transient stability analysis; parallel computing; shared memory and distributed memory machines

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    32
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
32
Top 10%
Top 10%
Average