  Understanding electrical energy demand at the consumer level plays an
important role in planning the distribution of electrical networks and offering
of off-peak tariffs, but observing individual consumption patterns is still
expensive. On the other hand, aggregated load curves are normally available at
the substation level. The proposed methodology separates substation aggregated
loads into estimated mean consumption curves, called typical curves, including
information given by explanatory variables. In addition, a model-based
clustering approach for substations is proposed based on the similarity of
their consumers typical curves and covariance structures. The methodology is
applied to a real substation load monitoring dataset from the United Kingdom
and tested in eight simulated scenarios.
