Application of Cray XMT for Power Grid Contingency Selection

نویسندگان

  • Yousu Chen
  • Shuangshuang Jin
  • Daniel Chavarría-Miranda
  • Zhenyu Huang
چکیده

Contingency analysis is a key function to assess the impact of various combinations of power system component failures. It involves combinatorial numbers of contingencies that exceed the capability of even very large supercomputing platforms. Therefore, it is critical to select credible contingency cases within the constraint of computing power. This paper presents a contingency selection method employing graph theory (edge betweenness centrality) to analyze power grid weighted graphs to remove low-impact components. The parallel implementation of the method was successfully demonstrated on the Cray XMT machine. The implementation takes advantage of the superior capabilities of the Cray XMT for graph-based problems and its programming features. This paper presents the performance and scalability of the Cray XMT and comparison with a cache-based, scalable, shared-memory machine.

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تاریخ انتشار 2009