An optimization-based data-driven approach is proposed to identify the unknown location(s) of destabilizing faults and attacks in power systems. The analysis in this paper kicks in at the critical moment where the presence of destabilizing fault or attack is detected within the power system; therefore, there is an immediate need to identify the location(s) of the affected generators or loads in order to enable proper and effective post-detection measures. The proposed method works in frequency-domain. It does not require prior knowledge about the number of affected location(s). It is accurate in identifying the correct locations and also in preventing false alarms. It is computationally more efficient than its time-domain counterparts. Importantly, it is well-suited to be implemented in a hierarchical fashion, with applications such as in wide area monitoring systems. Various case studies on IEEE 9 and IEEE 39 bus test systems verified the performance of the proposed algorithms.
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Amini et al. (2017) studied this question.
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