Review of Grid Stability Assessment Based on AI and a New Concept of Converter-Dominated Power System State of Stability Assessment
Wentao Liu, Tamás Kerekes, Tomislav Dragičević, Remus Teodorescu
Abstract
Artificial intelligence (AI) has been increasingly used for power system stability assessment due to its fast evaluation speed compared to conventional time-domain methods. This article reviews four types of classic grid stability assessment methods based on AI in the recent literature first, where different AI algorithms from the literature are summarized and compared. Moreover, as the number of power converters using grid forming control intensively increases in the modern system, the influence of the converter parameters on grid stability needs to be investigated. In this context, the concept of the converter-dominated power system state of stability (CDPS-SOS) assessment based on AI is qualitatively discussed. The CDPS-SOS assessment can reveal the system stability margin by considering the converter control parameters and grid bus voltages. Overall, this article aims to give an overview of AI-based stability assessment for the traditional grid and to provide a new stability assessment concept and inspiration for solving the challenges of future converter-dominated grids.