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Open Access research with a European policy impact...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by Strathclyde researchers, including by researchers from the European Policies Research Centre (EPRC).

EPRC is a leading institute in Europe for comparative research on public policy, with a particular focus on regional development policies. Spanning 30 European countries, EPRC research programmes have a strong emphasis on applied research and knowledge exchange, including the provision of policy advice to EU institutions and national and sub-national government authorities throughout Europe.

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ANN-based automatic contingency selection for electric power system

Lo, K.L. and Luan, W.P. and Given, M.J. and Bradley, M. and Wan, H. (2002) ANN-based automatic contingency selection for electric power system. COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 21 (2). pp. 193-207. ISSN 0332-1649

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Abstract

Automatic contingency selection aims to quickly predict the impact of a set of next contingencies on an electric power system without actually performing a full ac load flow. Artificial neural network methods have been employed to overcome the masking effects or slow execution associated with existing methods. However, the large number of input features for the ANN limits its applications to large power systems. In this paper, a novel feature selection method, named the Weak Nodes method, based on a heuristic approach is proposed for an ANN-based automatic contingency selection for electric power system, especially for the voltage ranking problem. Pre-contingency state variables of weak nodes in the power system are adopted as input features for the ANN. The method is tested on the 77 busbar NGC derived network by Counter-propagation Method and it is proved that it reduces the input features for ANN dramatically without losing ranking accuracy.