Decision tree based oscillatory stability assessment for large interconnected power systems

This paper deals with a new method for eigenvalue prediction of critical stability modes of power systems based on decision trees. Special interest is focused on inter-area oscillations of large-scale interconnected power systems. The existing methods for eigenvalue computations are time-consuming and require the entire system model that includes an extensive number of states. However, using decision trees, the oscillatory stability can be predicted based on a few selected inputs. Hereby, the outputs of the tree are assigned to the damping ratio of the critical inter-area eigenvalues. Decision trees are fast, easy to train and provide high accuracy for eigenvalue prediction.