  Current Energy systems located in almost all nations are going through a
radical transformation motivated by technological, environmental and
institutional needs. The introduction of novel technologies for energy
production and storing, the insurgence of climate change and the attention for
the introduction of low impact technologies in some countries are main factors
leading this transformation. Here we focus in particular on the introduction of
relatively small community energy systems based on solar energy that aim to
re-organize local energy systems to integrate distributed energy resources and
engage local communities. In each community, there is a set of producers and a
set of consumers (and a set of producers/consumers called prosumers). One of
the key aspects of the energetic communities is to maximise the energy that is
shared within the user. Thus, it is crucial to select the best
consumers/prosumers on the basis of their profile of consumption, in order to
minimize subsequent management of the energy once the community is built. Here
we describe the design of a recommender sysstem that is able to profile users
on the basis of their past profile for subsequent admission into the energetic
community. Experiments supporting this publication have been carried out under
the BDTI (Big Data Test Infrastructure) of the European Union. The contents of
this publication are the sole responsibility of authors and do not necessarily
reflect the opinion of the European Union.
