A Non-Direct Method for Contingency Ranking and Classification in Power Systems using Neural Networks

M.R. Haghifam, H. Falagi, H. Haroonabadi, J. Sahragard, and S.R. Razavi (Iran)


Power system security, Contingency ranking, Neural network


Power system security is assessed in three stages: contingencies prediction, contingencies ranking and severe contingencies evaluation. The most important in these is contingency ranking. In this stage contingencies are ranked based on their severities. In on-line control only the most severe contingencies are investigated. For contingency ranking many methods are presented in two categories: direct and in-direct methods. This paper presents an effective non-direct contingency ranking method based on neural network. The approach has been tested and evaluated on IEEE Reliability Test System (IEEE-RTS) with satisfactory results.

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