Analysis of SSR using artificial neural networks [power system simulation]

Artificial neural networks (ANNs) are being advantageously applied to power system analysis problems. They possess the ability to establish complicated input-output mappings through a learning process, without any explicit programming. In this paper, an ANN based method for subsynchronous resonance (SSR) analysis is presented. The designed ANN outputs a measure of the possibility of the occurrence of SSR and is fully trained to accommodate the variations of power system parameters over the entire operating range. The effectiveness of this approach is tested by experimenting on the first bench mark model proposed by IEEE Task Force on SSR.