- Oddbjørn Gjerde
- WP2 Lead
- SINTEF Energi AS
A systematic review of machine learning techniques related to local energy communities
Challenge and objective
- In summary, the contributions of this paper are as follows:
- A conceptualisation of LECs from a European perspective.
- An extensive review of state-of-the-art machine learning literature associated with LECs.
- Detailed applications of machine learning methods within LECs.
- An evaluation of and the future outlook on machine learning methods that are utilised in LECs.
- This result 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.
Reference in CINELDI
- A. Hernandez-Matheus, M. Löschenbrand, K. Berg, K., I. Fuchs, M. Aragüés-Peñalba, E. Bullich-Massagué, A. Sumper, A.: "A systematic review of machine learning techniques related to local energy communities", Renewable and Sustainable Energy Reviews, 170, p.112651.