4.7 Article

Fast Power System Cascading Failure Path Searching With High Wind Power Penetration

期刊

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
卷 11, 期 4, 页码 2274-2283

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2019.2953867

关键词

Power system faults; Power system protection; Wind power generation; Markov processes; Computational modeling; Acceleration; Cascading failure; power systems; algorithm acceleration; wind power; optimal power flow; Markov chain searching

资金

  1. National Key Research and Development Program of China [2016YFB0900100]
  2. Major Smart Grid Joint Project of Natural Science Foundation of China and State Grid [U1766212]
  3. Technical Project of the State Grid: Theoretical and Empirical Research of the Key Technology for the Whole Process Management of Power Grid Operation Risk Based on Multi Source Data Mining

向作者/读者索取更多资源

Cascading failures have become a severe threat to interconnected modern power systems. The ultrahigh complexity of the interconnected networks is the main challenge toward the understanding and management of cascading failures. In addition, high penetration of wind power integration introduces large uncertainties and further complicates the problem into a massive scenario simulation problem. This article proposes a framework that enables a fast cascading path searching under high penetration of wind power. In addition, we ease the computational burden by formulating the cascading path searching problem into a Markov chain searching problem and further use a dictionary-based technique to accelerate the calculations. In detail, we first generate massive wind generation and load scenarios. Then, we utilize the Markov search strategy to decouple the problem into a large number of DC power flow (DCPF) and DC optimal power flow (DCOPF) problems. The major time-consuming part, the DCOPF and the DCPF problems, is accelerated by the dynamic construction of a line status dictionary (LSD). The information in the LSD can significantly ease the computation burden of the following DCPF and DCOPF problems. The proposed method is proven to be effective by a case study of the IEEE RTS-79 test system and an empirical study of China's Henan Province power system.

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