Estimación de la carga de transformadores de potencia utilizando una red neuronal artificial

Abstract

This paper presents a methodology for load estimation of power transformers by means of artificial neural networks. To implement the proposed methodology the data of two power transformers, located in different geographical areas and with different operational conditions, were considered. The load estimation methodology was implemented using historical data provided by the company Interconexión Eléctrica S.A. (ISA). To predict the load curves a neural network was trained using MATLAB, being able to fit a load curve with daily and weekly prediction times. The proposed method allows the estimation of load curve values in power transformers with an average percent relative error of around 10%. The method described in this paper can be applied to other equipment with similar operating characteristics.