Efficient algorithm for online N - 2 power grid contingency selection

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.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Mechanical Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2014

Author dc:creator

• Kaplunovich, Petr A. (Petr Alexandrovich)

Advisor dc:contributor.advisor

• Konstantin Turitsyn.

• Mechanical Engineering.

Statement dc:rights

• 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.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/88388

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/88388