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Transient stability assessment (TSA) has always been a fundamental means forensuring the secure and stable operation of power systems. Due to theintegration of new elements such as power electronics, electric vehicles andrenewable power generations, dynamic characteristics of power systems arebecoming more and more complex, which makes TSA an increasingly urgent task.Since traditional time-domain simulations and direct method cannot meet theactual operation requirements of power systems, data-driven TSA has attractedgrowing attention from both academia and industry. This paper makes acomprehensive review from the following four aspects: feature extraction andselection, model construction, online learning and rule extraction; and then,summarizes the challenges and prospects for future research; finally, draws theconclusions of this review. This review will be beneficial for relevantresearchers to better understand the research status, key technologies andexisting challenges in the field.

A critical review of data-driven transient stability assessment of power systems: principles, prospects and challenges