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[01-02, 1998] 

Journal of Electrical Engineering, Vol 49, 01-02 (1998) 3-10

APPLICATIONS OF NEURAL NETWORKS TO POWER SYSTEM CONTROL

Michal Kolcun - Radoslav Benč - Peter Szathmáry

   The authors propose an overview of their research in the area of artificial neural network (ANN) applications to power system control. Application possibilities of ANNs are discussed. Then, a description of three projects carried out at the Department of Power Engineering FEI, Technical University in Kosice is given.
The first part of the presentation is a brief description of an ANN based tool for fast, on-line contingency analysis. In this tool, the ANN acts as a classifier, which detects possible unsafe consequences of single line outage in power system. Two different approaches to the problem are described and test results are shown.
The second approach is an application of ANN to load flow calculation. Load flow studies are important in power system planning, control and operation. After training, the ANN is able to approximate bus voltages when active and reactive loads are presented. The approach was tested on a simple power system model.
In the third part, a short term load forecaster is described. In this approach, an ANN is the main component of the forecaster. Choice of training data, normalisation, and design of the neural network are discussed. The load forecaster performed load forecasts for the Slovak Republic for the year 1996. Simulation results, practical experiences, as well as possible improvements are shown.

Keywords: power system control, neural networks, contingency analysis, load flow, load forecasting, backpropagation


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