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A systematic review of machine learning techniques related to local energy communities

Abstract

In recent years, digitalisation has rendered machine learning a key tool for improving processes in several sectors, as in the case of electrical power systems. Machine learning algorithms are data-driven models based on statistical learning theory and employed as a tool to exploit the data generated by the power system and its users. Energy communities are emerging as novel organisations for consumers and prosumers in the distribution grid. These communities may operate differently depending on their objectives and the potential service the community wants to offer to the distribution system operator. This paper presents the conceptualisation of a local energy community on the basis of a review of 25 energy community projects. Furthermore, an extensive literature review of machine learning algorithms for local energy community applications was conducted, and these algorithms were categorised according to forecasting, storage optimisation, energy management systems, power stability and quality, security, and energy transactions. The main algorithms reported in the literature were analysed and classified as supervised, unsupervised, and reinforcement learning algorithms. The findings demonstrate the manner in which supervised learning can provide accurate models for forecasting tasks. Similarly, reinforcement learning presents interesting capabilities in terms of control-related applications.
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Category

Academic article

Language

English

Author(s)

  • Alejandro Hernandez-Matheus
  • Markus Löschenbrand
  • Kjersti Berg
  • Ida Fuchs
  • Mònica Aragüés-Peñalba
  • Eduard Bullich-Massagué
  • Andreas Sumper

Affiliation

  • SINTEF Energy Research / Energisystemer
  • Polytechnic University of Catalonia
  • Norwegian University of Science and Technology

Year

2022

Published in

Renewable and Sustainable Energy Reviews

ISSN

1364-0321

Volume

170

Issue

112651

View this publication at Norwegian Research Information Repository