Quick and effective multiple contingency screening algorithm based on long-tailed distribution

This study proposes a quick and effective algorithm for screening severe N − 2 contingency, thus avoiding exhausting analysis of all conceivable N − 2 contingencies. First, the index of overload contribution rate (OCR) is developed on the basis of distribution factor, which is discovered to be long-tailed distributed by statistics. Then, by fully exploiting the discovered feature, the so-called technique of combination of partitioned data sets (TCPDS) is designed and described. The core of the contingency screening algorithm is to apply the TCPDS to the OCR. Moreover, an index system is established to evaluate the proposed algorithm. Finally, the proposed algorithm is proved to be effective and efficient by the index system when applied to some practical power systems.