A self organizing map (SOM) based electric load classification

Mahdi Farhadi
2018 Facta universitatis - series Electronics and Energetics  
It is of vital importance to use proper training data to perform accurate shortterm load forecasting (STLF) based on artificial neural networks. The pattern of the loads which are used for the training of Kohonen Self Organizing Map (SOM) neural network in STLF models should be of the highest similarity with the pattern of the electric load of the forecasting day. In this paper, an electric load classifier model is proposed which relies on the pattern recognition capability of SOM. The
more » ... ce of the proposed electric load classifier method is evaluated by Iran electric grid data. The proposed method requires a very few number of training samples for training the Kohonen neural network of the STLF model and can accurately predict electric load in the network.
doi:10.2298/fuee1804571f fatcat:xgcfxd2drvex3fn4uy6tktvg7m