Application of computational intelligence techniques for load shedding in power systems: A review

Power system transient stability margin estimation using neural networks

Transient stability assessment of power systems described with detailed models using neural networks

Online transient stability assessment (TSA) of a power system is not yet feasible due to the intensive computation involved. Artificial neural networks (ANN) have been proposed as one of the approaches to this problem because of their ability to quickly map nonlinear relationships between the input data and the output. In this paper a review of the previously published papers on TSA using ANN is presented. The paper also reports the results of the application of ANN to the problem of TSA of a 10 machine 39 bus system.

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Transient stability assessment using artificial neural networks

Applications of artificial intelligence in power systems

The paper presents an evaluation of the effectiveness of artificial neural networks for rapid determination of critical clearing times for practical networks with varying line outages and load patterns. Studies are reported on the performance of artificial neural networks which have been trained using previously proposed and new training items. It is concluded that artificial neural networks have difficulty in returning consistently accurate answers under varying network conditions. >

G.N. Allen

Papers

Effectiveness of artificial neural networks for first swing stability determination of practical systems