Parallel solution of large sparse matrix equations and parallel power flow

Author

Wu, Jun Qiang ; Bose, Anjan

Author_Institution

Arizona State Univ., Tempe, AZ, USA

Volume

10

Issue

3

fYear

1995

fDate

8/1/1995 12:00:00 AM

Firstpage

1343

Lastpage

1349

Abstract

A very efficient parallel LU factorization and substitution algorithm for solving large sparse network equations on shared memory multi-processor parallel computers is presented. By rearranging the order of the computations, better parallelism is obtained out of the traditionally sequential method. Performance results on an actual parallel computer are presented and discussed. Parallel gains for the power flow solution using Newton´s and fast decoupled methods are presented to demonstrate it´s effectiveness. Better speedup gains are obtained for larger systems and speedup of over 13 for Newton´s power flow on a 20 processor shared memory computer has been obtained

Keywords

Newton method; load flow; parallel algorithms; power system analysis computing; shared memory systems; sparse matrices; LU factorization; Newton´s method; fast decoupled method; large sparse matrix equations; parallel power flow; power systems; shared memory multi-processor parallel computers; substitution algorithm; Computer networks; Concurrent computing; Equations; Load flow; Parallel algorithms; Parallel processing; Power engineering; Power engineering computing; Power system analysis computing; Sparse matrices;

fLanguage

English

Journal_Title

Power Systems, IEEE Transactions on

Publisher

ieee

ISSN

0885-8950

Type

jour

DOI

10.1109/59.466519

Filename

466519