Data-Driven Online Stability Diagnostics for Parallel Grid-Connected Converters in Weak Grid

This paper presents a data-driven online diagnostics method to identify the stability of parallel grid-connected converters. Specifically, the dataset consists of summed output current of all the parallel converters at the point of common coupling (PCC) and state label. Neural network algorithm is applied to infer steady state of parallel converters. The case study validates accuracy and efficiency of the proposed method.