NDLI: GPU-based two-step preconditioning for conjugate gradient method in power flow

Content Provider	IEEE Xplore Digital Library
Author	Xue Li Fangxing Li
Copyright Year	2015
Description	Author affiliation: Dept. of Electr. Eng. & Comput. Sci., Univ. of Tennessee, Knoxville, Knoxville, TN, USA (Xue Li; Fangxing Li)
Abstract	With the development of the modern power system and the computational hardware, the industrial and research communities are more interested in simulating larger and more complicated power grids. Various iterative solvers for linear systems have been investigated with power system applications for its parallel potential in large scale linear computations. They usually require preconditioning to improve their convergence rate. This work will discuss three preconditioners: Jacobi preconditioner, Chebyshev preconditioner, and a two-step preconditioner with Jacobi first and then Chebyshev. The results show that the two-step preconditioner provides better preconditioning effects than using any of them alone. Besides, the GPU implementation of the iterative solver and preconditioners shows performance improvement over Matlab implementation. The improvement can reach up to 8.9× with the two-step preconditioner for the largest test system. These results demonstrate great potential for both preconditioned iterative solver and GPU application in power system simulations.
Starting Page	1
Ending Page	5
File Size	186465
Page Count	5
File Format	PDF
ISBN	9781467380409
DOI	10.1109/PESGM.2015.7286544
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Jacobian matrices Graphics processing units Chebyshev approximation Load flow Power system stability Gradient methods Iterative methods precondition Conjugate gradient method GPU iterative solver power flow
Content Type	Text
Resource Type	Article

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