Algorithms for efficient vectorization of repeated sparse power system network computations
Author
Aykanat, Cevdet
Özgü, Ö.
Güven, N.
Date
1995Source Title
IEEE Transactions on Power Systems
Print ISSN
0885-8950
Electronic ISSN
1558-0679
Publisher
IEEE
Volume
10
Issue
1
Pages
448 - 456
Language
English
Type
ArticleItem Usage Stats
135
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views
86
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Abstract
Standard sparsity-based algorithms used in power system
appllcations need to be restructured for efficient vectorization
due to the extremely short vectors processed. Further, intrinsic
architectural features of vector computers such as chaining and
sectioning should also be exploited for utmost performance. This
paper presents novel data storage schemes and vectorization alsorim
that resolve the recurrence problem, exploit chaining and
minimize the number of indirect element selections in the repeated
solution of sparse linear system of equations widely encountered
in various power system problems. The proposed schemes are
also applied and experimented for the vectorization of power mismatch
calculations arising in the solution phase of FDLF which involves
typical repeated sparse power network computations. The
relative performances of the proposed and existing vectorization
schemes are evaluated, both theoretically and experimentally on
IBM 3090ArF.
Keywords
AlgorithmsCalculations
Computer Architecture
Computer Hardware
Data Storage Equipment
Data Structures
Electric Load Flow
Fortran (Programming Language)
Optimization
Parallel Processing Systems
Pipeline Processing Systems
Vectors Efficient Vectorization
Fast Decoupled Load Flow
Forward/backward Substitution
Sparse Linear System
Sparse Power System Network
Vector Processing
Electric Power Systems
Vector Computers
Matrix
Factorization
Flow
Permalink
http://hdl.handle.net/11693/10801Published Version (Please cite this version)
http://dx.doi.org/10.1109/59.373970Collections
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