Contingency ranking for voltage collapse using parallel self-organizing hierarchical neural network (original) (raw)

International Journal of Electrical Power & Energy Systems, 2001

Abstract

On-line monitoring of the power system voltage security has become a vital factor for electric utilities. This paper proposes a voltage contingency ranking approach based on parallel self-organizing hierarchical neural network (PSHNN). Loadability margin to voltage collapse following a contingency has been used to rank the contingencies. PSHNN is a multi-stage neural network where the stages operate in parallel rather

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