Online voltage stability monitoring using Artificial Neural Network

This paper presents an application of Artificial Neural Network (ANN) for monitoring power system voltage stability. The training of ANN is accomplished by adapting information received from local and remote measurements as inputs and fast indicators providing voltage stability information of the whole power system and one at each particular bus as outputs. The use of feature reduction techniques can decrease the number of features required and thus reduce the number of system quantities needed to be measured and transmitted. In this paper, the effectiveness of the proposed algorithm is tested under a large number of random operating conditions on the standard IEEE 14-bus system and the results are encouraging. Fast performance and accurate evaluation of voltage stability indicators have been obtained. Finally, the idea of applying load shedding based on voltage stability indicator as one of potential countermeasures is described.