Cost Analysis of Transformer´s Main Material Weight with Artificial Neural Network (ANN)

Transformer is one of the vital components in electrical network which play important role in the power system. The continuous performance of transformers is necessary for retaining the network reliability, forecasting its costs for manufacturer and industrial companies. The major amount of transformer costs are related to its raw materials, so the cost estimation process of transformers are based on amount of used raw material. This paper presents a new method to estimate the weight of main materials for transformers. The method is based on Multilayer Perceptron Neural Network (MPNN) with sigmoid transfer function. The Levenberg-Marquard (LM) algorithm is used to adjust the parameters of MPNN. The required training data are obtained from transformer company.