GPU-Based Batch LU-Factorization Solver for Concurrent Analysis of Massive Power Flows

In many power system applications, such as N-x static security analysis and Monte-Carlo-simulation-based probabilistic power flow (PF) analysis, it is a very time-consuming task to analyze massive number of PFs on identical or similar network topology. This letter presents a novel GPU-accelerated ba...

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Bibliographic Details
Published in:IEEE transactions on power systems 2017-11, Vol.32 (6), p.4975-4977
Main Authors: Zhou, Gan, Bo, Rui, Chien, Lungsheng, Zhang, Xu, Shi, Fei, Xu, Chunlei, Feng, Yanjun
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Bandwidth
Degree of parallelism
graphics processing unit (GPU)
Graphics processing units
Load flow
LU factorization
parallel computing
Parallel processing
power flow
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Summary:In many power system applications, such as N-x static security analysis and Monte-Carlo-simulation-based probabilistic power flow (PF) analysis, it is a very time-consuming task to analyze massive number of PFs on identical or similar network topology. This letter presents a novel GPU-accelerated batch LU-factorization solver that achieves higher level of parallelism and better memory-access efficiency through packaging massive number of LU-factorization tasks to formulate a new larger-scale problem. The proposed solver can achieve up to 76 times speedup when compared to KLU library and lays a critical foundation for massive-PFs-solving applications.
ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2017.2662322