The paper proposes a novel method using a neuro-fuzzy based model for identification of `off-standard' configurations of large electric distribution network components. The method provides an automatic procedure for off-line processing of historical loading data that are made available by an existing monitoring and control system of the grid. The method is based on a version of Simpson's Min-Max paradigm, optimized with respect to clustering performance measured by a suitable compactness-separability index.
A neuro-fuzzy approach to the planning of electric distribution networks / Fracassi, G.L., FRATTALE MASCIOLI, F.M., Lamedica, R., Martinelli, G., Prudenzi, A., Regoli, M., Rizzi, A.. - STAMPA. - 1:(1998), pp. 79-83. (1998 IEEE International Joint Conference on Neural Networks. Anchorage, AK, USA 4 May 1998through9 May 1998) [10.1109/IJCNN.1998.682240].
A neuro-fuzzy approach to the planning of electric distribution networks
FRATTALE MASCIOLI, Fabio Massimo;LAMEDICA, Regina;RIZZI, Antonello
1998
Abstract
The paper proposes a novel method using a neuro-fuzzy based model for identification of `off-standard' configurations of large electric distribution network components. The method provides an automatic procedure for off-line processing of historical loading data that are made available by an existing monitoring and control system of the grid. The method is based on a version of Simpson's Min-Max paradigm, optimized with respect to clustering performance measured by a suitable compactness-separability index.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
