Implementation of a massively parallel dynamic security assessment platform for large-scale grids

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Title: Implementation of a massively parallel dynamic security assessment platform for large-scale grids
Authors: Konstantelos, I
Jamgotchian, G
Tindemans, S
Duchesne, P
Cole, S
Merckx, C
Strbac, G
Panciatici, P
Item Type: Journal Article
Abstract: This paper presents a computational platform for dynamic security assessment (DSA) of large electricity grids, developed as part of the iTesla project. It leverages High Performance Computing (HPC) to analyze large power systems, with many scenarios and possible contingencies, thus paving the way for pan-European operational stability analysis. The results of the DSA are summarized by decision trees of 11 stability indicators. The platform’s workflow and parallel implementation architecture is described in detail, including the way commercial tools are integrated into a plug-in architecture. A case study of the French grid is presented, with over 8000 scenarios and 1980 contingencies. Performance data of the case study (using 10,000 parallel cores) is analyzed, including task timings and data flows. Finally, the generated decision trees are compared with test data to quantify the functional performance of the DSA platform.
Issue Date: 8-Sep-2016
Date of Acceptance: 27-Aug-2016
URI: http://hdl.handle.net/10044/1/39765
DOI: https://dx.doi.org/10.1109/TSG.2016.2606888
ISSN: 1949-3061
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Start Page: 1417
End Page: 1426
Journal / Book Title: IEEE Transactions on Smart Grid
Volume: 8
Issue: 3
Copyright Statement: © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works.
Sponsor/Funder: Commission of the European Communities
Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: 283012
EP/M015025/1
Keywords: Science & Technology
Technology
Engineering, Electrical & Electronic
Engineering
High performance computing
Monte Carlo methods
power system simulation
power system stability
DECISION TREES
0906 Electrical And Electronic Engineering
0915 Interdisciplinary Engineering
Publication Status: Published
Appears in Collections:Faculty of Engineering
Electrical and Electronic Engineering
Centre for Environmental Policy
Faculty of Natural Sciences



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