Efficient algorithm for online N - 2 power grid contingency selection

Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2014.

Bibliographic Details
Main Author: Kaplunovich, Petr A. (Petr Alexandrovich)
Other Authors: Konstantin Turitsyn.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2014
Subjects:
Online Access:http://hdl.handle.net/1721.1/88388
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author Kaplunovich, Petr A. (Petr Alexandrovich)
author2 Konstantin Turitsyn.
author_facet Konstantin Turitsyn.
Kaplunovich, Petr A. (Petr Alexandrovich)
author_sort Kaplunovich, Petr A. (Petr Alexandrovich)
collection MIT
description Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2014.
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spelling mit-1721.1/883882019-04-11T12:06:33Z Efficient algorithm for online N - 2 power grid contingency selection Kaplunovich, Petr A. (Petr Alexandrovich) Konstantin Turitsyn. Massachusetts Institute of Technology. Department of Mechanical Engineering. Massachusetts Institute of Technology. Department of Mechanical Engineering. Mechanical Engineering. Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2014. Cataloged from PDF version of thesis. Includes bibliographical references (pages 55-57). Multiple element outages (N - k contingencies) have caused some of the most massive blackouts and disturbances in the power grid. Such outages affect millions of people and cost the world economy billions of dollars annually. The impact of the N - k contingencies is anticipated to grow as the electrical power grid becomes increasingly more loaded. As the result power system operators face the need for advanced techniques to select and mitigate high order contingencies. This study presents a novel algorithm for the fast N - 2 contingency selection to address this problem. The developed algorithm identifies all potentially dangerous contingencies with zero missing rate. The complexity of the algorithm is shown to be of the same order as the complexity of N - 1 contingency selection, which makes it much more efficient than brute force enumeration. The study first derives the equations describing the set of the dangerous N - 2 contingencies in the symmetric form and presents an effective way to bound them. The derived bounding technique is then used to develop an iterative pruning algorithm. Next, the performance of the algorithm is validated using various grid cases under different load conditions. The efficiency of the algorithm is shown to be rather promising. For the Summer Polish grid case with more than 3500 lines it manages to reduce the size of the contingency candidates set by the factor of 1000 in just 2 iterations. Finally, the reasons behind the efficiency of the algorithm are discussed and intuition around the connection of its performance to the grid structure is provided. by Petr A. Kaplunovich. S.M. 2014-07-11T21:08:09Z 2014-07-11T21:08:09Z 2014 2014 Thesis http://hdl.handle.net/1721.1/88388 881244021 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 57 pages application/pdf Massachusetts Institute of Technology
spellingShingle Mechanical Engineering.
Kaplunovich, Petr A. (Petr Alexandrovich)
Efficient algorithm for online N - 2 power grid contingency selection
title Efficient algorithm for online N - 2 power grid contingency selection
title_full Efficient algorithm for online N - 2 power grid contingency selection
title_fullStr Efficient algorithm for online N - 2 power grid contingency selection
title_full_unstemmed Efficient algorithm for online N - 2 power grid contingency selection
title_short Efficient algorithm for online N - 2 power grid contingency selection
title_sort efficient algorithm for online n 2 power grid contingency selection
topic Mechanical Engineering.
url http://hdl.handle.net/1721.1/88388
work_keys_str_mv AT kaplunovichpetrapetralexandrovich efficientalgorithmforonlinen2powergridcontingencyselection