Small-signal stability assessment for large power systems using computational intelligence

This paper introduces newly developed methods for on-line oscillatory stability assessment in large interconnected power systems. Special interest is focused on the fast prediction of critical inter-area oscillatory modes. Instead of eigenvalue computation using the complete power system model, the new proposed OSA methods are based on computational intelligence such as neural networks, neuro fuzzy methods, and decision trees. Computational intelligence needs only a small set of selected system information and can easily be implemented as fast on-line assessment tool.