Towards a Recommender System for Profiling Users in a Renewable Energetic Community
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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.
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