An empirical model for forecasting electrie power consumption is forrnulated. The research concerns the preparation and optimal selection of characteristic variables. Prototype patteriis of eleetric power consumption over a day are described by proper by encoding the day-types and their self-organised adaptation to the data recorded in the past. In this procedure, holidays are treated by specific prototype patterns. The influence of the environmental temperature on the consumed power is accounted for by including the extrerne vahies of temperature in a day into prototype patterns. These patterns are employed as parameters of a norrnalised radial basis function neural network, which is used to forecasting the consumption process. The performance of forecasting and the applicability of various input variables is tested, based on one- and four-year-long records of electrie power consumption in Slovenia.