This paper presents a neural-network based method for evaluating on-line power system voltage stability. Starting with an appropriate linearized model of the system, the proximity of the power system to the voltage instability is quantified by using a suitable index. Then, a three-layer feedforward neural network is trained to learn the underlying features of the voltage stability phenomenon. Once trained, the neural network provides the above mentioned voltage stability index as output to a pre-defined set of input variables that are known to influence directly the voltage stability conditions of the load area. The. effectiveness of the proposed approach has been tested on the 39-busbar New England test system.

Towards a neural network based voltage stability assessment

Trovato, M.
1996

Abstract

This paper presents a neural-network based method for evaluating on-line power system voltage stability. Starting with an appropriate linearized model of the system, the proximity of the power system to the voltage instability is quantified by using a suitable index. Then, a three-layer feedforward neural network is trained to learn the underlying features of the voltage stability phenomenon. Once trained, the neural network provides the above mentioned voltage stability index as output to a pre-defined set of input variables that are known to influence directly the voltage stability conditions of the load area. The. effectiveness of the proposed approach has been tested on the 39-busbar New England test system.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11589/11646
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