On-line Voltage Instability Prediction using an Artificial Neural Network

Paper i proceeding, 2019

In this paper, a predictive method to detect voltage instability using an artificial neural network is presented. The proposed method allows transmission  system operators to predict long-term voltage instability far before the system voltage stability has been degraded, allowing swift and cost-effective control actions. The predictor is tested and trained on the Nordic32 test system for a wide range of different contingencies. The predictor proves to be accurate in providing early warnings of impending voltage instability, allowing 96.3 % of all test cases being correctly classified only seconds after a contingency. The method is proposed to be used as an effective tool for supplementary voltage instability detection for transmission system operators.