  Adoption of smart meters is a major milestone on the path of European
transition to smart energy. The residential sector in France represents
$\approx$35\% of electricity consumption with $\approx$40\% (INSEE) of
households using electrical heating. The number of deployed smart meters Linky
is expected to reach 35M in 2021. In this manuscript we present an analysis of
676 households with an observation period of at least 6 months, for which we
have metadata, such as the year of construction and the type of heating and
propose a Bayesian model of the electrical consumption conditioned on
temperature that allows to disaggregate the heating component from the
electrical load curve in an unsupervised manner. In essence the model is a
mixture of piece-wise linear models, characterised by a temperature threshold,
below which we allow a mixture of two modes to represent the latent state
home/away.
