Transient stability prediction of power system; a review on methods, classification and considerations

Transient stability is a prominent aspect of power system stability and therefore instability prediction has been the subject of a vast amount of research and many publications. In the published literature, various aspects of this topic including principals, methodologies, accuracy and practical consideration for implementation are investigated. However, a comprehensive review article that summarizes and compares these issues has yet been unpublished. Accordingly, in this article, the relevant publications are reviewed, categorized and their advantages and disadvantages are highlighted. The methods used in these articles can be classified into four main categories: time-domain, transient energy function, curve-fitting, and machine learning. For each class, the characteristics of the cluster are specified. Moreover, the comprehensive comparison tables are introduced to show the additional information such as test systems, response times and required infrastructures. Ultimately, the issues such as trend of papers during recent years, common test systems and the main gaps in the literature are addressed.