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Ingeniare. Revista chilena de ingeniería

versión On-line ISSN 0718-3305

Resumen

VELASQUEZ, Juan D; DYNER, Isaac  y  SOUZA, Reinaldo C. ELECTRICITY SPOT PRICE MODELLING IN BRASIL USING AN AUTOREGRESSIVE NEURAL NETWORK. Ingeniare. Rev. chil. ing. [online]. 2008, vol.16, n.3, pp.394-403. ISSN 0718-3305.  http://dx.doi.org/10.4067/S0718-33052008000300002.

An autoregressive neural network model is estimated for the monthly Brazilian electricity spot price, which describes the prices dynamics better than a linear autoregressive model and a classical multilayer perceptron using the same input and neurons in the hidden layer. The proposed model is specified using a statistical procedure based on a likelihood ratio test. The model passes a battery of diagnostic tests. The proposed specification procedure allows us to select the number of units in hidden layer and the inputs to the neural network based on statistical tests, taking into account the number of data and the model fitting to the price time series. The final model specification demonstrates that the price for the next month is a nonlinear function of the current price, the current energy inflow, and the energy saved in the equivalent reservoir in the current month and two months ago.

Palabras clave : Autoregressive neural network; specification procedure; electricity spot price; nonlinear time series modelling.

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