Abstrocr-Traditional methods for estimating future values of demand and energy do not normally take into account the effect of the so-cailed exogenous variables, which include Ioad geographical location, seasonal variations, availability restrictions of energy and summer time schedules. This work proposes a methodology for assessing the impact of these external variables on the estimation of future values of demand and energy, with a view to improving current practices which dictate demand and energy purchases in both the short term and the medium term. The load curve i s broken into components associated with each one of the exogenous variables. The future behavior of each component is estimated through Artificial Neural Networks and the estimated global curve is obtained by aggregating the various components back together.
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