A Sparsity-Preserving Spectral Preconditioner for Power Ow Analysis

dc.authorscopusid 35782637700
dc.authorscopusid 57188731788
dc.contributor.author Yetkin,E.F.
dc.contributor.author Yetkin, Emrullah Fatih
dc.contributor.author Daʇ,H.
dc.contributor.other Business Administration
dc.date.accessioned 2024-10-15T19:41:52Z
dc.date.available 2024-10-15T19:41:52Z
dc.date.issued 2016
dc.department Kadir Has University en_US
dc.department-temp Yetkin E.F., Caferaʇa Mah., Dalga Sok., Eren Apt. No 4 D 1, Kadiköy, Istanbul, Turkey; Daʇ H., Department of Management Information Systems, Faculty of Engineering and Natural Sciences, Kadir Has University, Istanbul, Turkey en_US
dc.description.abstract Due to the ever-increasing demand for more detailed and accurate power system simulations, the dimensions of mathematical models increase. Although the traditional direct linear equation solvers based on LU factorization are robust, they have limited scalability on the parallel platforms. On the other hand, simulations of the power system events need to be performed at a reasonable time to assess the results of the unwanted events and to take the necessary remedial actions. Hence, to obtain faster solutions for more detailed models, parallel platforms should be used. To this end, direct solvers can be replaced by Krylov subspace methods (conjugate gradient, generalized minimal residuals, etc.). Krylov subspace methods need some accelerators to achieve competitive performance. In this article, a new preconditioner is proposed for Krylov subspace-based iterative methods. The proposed preconditioner is based on the spectral projectors. It is known that the computational complexity of the spectral projectors is quite high. Therefore, we also suggest a new approximate computation technique for spectral projectors as appropriate eigenvalue-based accelerators for efficient computation of power ow problems. The convergence characteristics and sparsity structure of the preconditioners are compared to the well-known black-box preconditioners, such as incomplete LU, and the results are presented. ©2016 Tübitak. en_US
dc.identifier.citationcount 0
dc.identifier.doi 10.3906/elk-1304-123
dc.identifier.endpage 383 en_US
dc.identifier.issn 1300-0632
dc.identifier.issue 2 en_US
dc.identifier.scopus 2-s2.0-84962547729
dc.identifier.scopusquality Q3
dc.identifier.startpage 370 en_US
dc.identifier.uri https://doi.org/10.3906/elk-1304-123
dc.identifier.uri https://hdl.handle.net/20.500.12469/6474
dc.identifier.volume 24 en_US
dc.identifier.wosquality Q4
dc.language.iso en en_US
dc.publisher Turkiye Klinikleri Journal of Medical Sciences en_US
dc.relation.ispartof Turkish Journal of Electrical Engineering and Computer Sciences en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.scopus.citedbyCount 0
dc.subject Iterative methods en_US
dc.subject Krylov accelerators en_US
dc.subject Power ow analysis en_US
dc.subject Sparse approximation en_US
dc.subject Spectral projectors en_US
dc.title A Sparsity-Preserving Spectral Preconditioner for Power Ow Analysis en_US
dc.type Article en_US
dspace.entity.type Publication
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