Artificial Neural Network-based Small Signal Stability Analysis of Power Systems

摘要

The massive integration of renewable energy sources, due to their stochastic nature, is introducing unprecedented changes to power system dynamics. Near real-time small signal stability analysis can be crucial to identify the dominant modes and activate preventive control actions. However, model-based methods are time consuming for large scale systems and unfeasible for real-time operation.This paper proposes a black box approach for fast small signal stability analysis in power systems, based on artificial neural networks. A training set is generated from the results of modal analyses in a wide range of scenarios. Once trained, the neural network can predict, fast and accurately, the required stability indices. The effectiveness of the proposed method is tested on the WSCC 9-bus network.