Aristidou, P orcid.org/0000-0003-4429-0225 and Hug, G (2016) Accelerating the computation of critical eigenvalues with parallel computing techniques. In: Power Systems Computation Conference (PSCC), 2016. Genova, Italy, 20-24 Jun 2016, 2016 Power Systems Computation Conference (PSCC). Power Systems Computation Conference ISBN 978-88-941051-2-4
Abstract
Eigenanalysis of power systems is frequently used to study the effect and tune the response of existing controllers, or to guide the design of new controllers. However, recent developments in the area lead to the necessity of studying larger power system models, resulting from the interconnection of transmission networks or the joint consideration of transmission and distribution networks. Moreover, these models include new types of controls, mainly based on power electronic interfaces, which are expected to provide significant support in the future. The consequence is that the size and complexity of these models challenge the computational efficiency of existing eigenanalysis methods. In this paper, a procedure is proposed that uses domain decomposition and parallel computing methods, to accelerate the computation of eigenvalues in a selected region of the complex plane with iterative eigenanalysis methods. The proposed algorithm is validated on a small transmission system and its performance is assessed on a large-scale, combined transmission and distribution system.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. |
Keywords: | Eigenanalysis; domain decomposition; parallel computing; OpenMP; implicitly restarted Arnoldi |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 14 Oct 2016 13:23 |
Last Modified: | 17 Jan 2018 23:32 |
Published Version: | http://dx.doi.org/10.1109/PSCC.2016.7540976 |
Status: | Published |
Publisher: | Power Systems Computation Conference |
Identification Number: | 10.1109/PSCC.2016.7540976 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:105995 |