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Unlocking residential building flexibility potential applying NILM techniques to smart meters data.

THESIS OPPORTUNITY […]

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In typical Renewable Energy Communities (RECs), members are mostly residential users and only aggregated data on electrical consumption is available. Specific consumption for heating and cooling is not monitored separately, which limits the assessment of future potential for RECs, such as providing grid flexibility services. This thesis project proposes the use of Nonintrusive Load Monitoring (NILM) techniques – belonging to the Advanced Data Analytics family – to identify and isolate energy consumption attributable to heating and cooling, improving the management and efficiency of RECs.

The student will benefit from synergies with LEAP – Laboratorio Energia e Ambiente Piacenza, already active on several projects on the topic.

Area di competenza
Smart Energy Systems

Responsabili

Filippo Bovera (filippo.bovera@polimi.it) – Politecnico di Milano

Matteo Zatti (matteo.zatti@polimi.it) – LEAP

Gaia Martoriello (gaia.martoriello@polimi.it) – LEAP

Marco Gabba (marco.gabba@polimi.it) – LEAP

Competenze richieste

Energy communities, machine learning, electricity markets

Background in Energy/Electrical Engineering

Data di inizio presunta
As soon as possible

Durata
9-12 months (full-thesis). Short thesis will be considered if requested.

Maggiori informazioni
Weekly meeting online or in presence.


CANDIDATI