Towards a Recommender System for Profiling Users in a Renewable Energetic Community
Pietro Hiram Guzzi, Francesco Chiodo

TL;DR
This paper proposes a recommender system designed to profile users based on their energy consumption patterns to optimize user selection in small solar-powered energy communities, supporting efficient energy sharing.
Contribution
It introduces a novel user profiling recommender system tailored for renewable energy communities, leveraging past consumption data to improve community energy management.
Findings
Supported by experiments on EU's BDTI infrastructure
Demonstrates effective user profiling for energy community integration
Aims to enhance energy sharing efficiency within communities
Abstract
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…
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Taxonomy
TopicsSmart Grid Energy Management · Green IT and Sustainability · IoT and Edge/Fog Computing
