SARX Model Application for Industrial Power Demand Forecasting in Brazil Aplicação do Modelo SARX para Previsão do Consumo Industrial de Energia Elétrica no Brasil

The objective of this paper is to propose the appli cation of the SARX model to arrive at industrial power consumption forecasts in Brazil, w hich are critical to support decisionmaking in the energy sector, based on technical, ec onomic and environmentally sustainable grounds. The proposed model has a seasonal component and considers the influence of exogenous variables on the projection of the depend ent variable and utilizes an autoregressive process for residual modeling so as to improve its explanatory power. Five exogenous variables were included: industrial capacity utiliz ation, industrial electricity tariff, industrial real revenues, exchange rate, and machinery and equ ipment inflation. In addition, the model assumed that power forecast was dependent on its own time lags and also on a dummy variable to reflect 2009 economic crisis. The study used 84 monthly observations, from January 2003 to December 2009. The backward method was used to select exogenous variables, assuming a 0.10 descriptive value. The r esults showed an adjusted coefficient of determination of 93.9% and all the estimated coeffi cients were statistically significant at a 0.10 descriptive level. Forecasts were also made fr om January to May 2010 at a 95% confidence interval, which included actual consumpt ion values for this period. The SARX model has demonstrated an excellent performance for industrial power consumption