Machine learning-based short-term net load forecasting for residential buildings with integrated photovoltaic systems

Georgios Tziolis

doi:10.1016/j.egyr.2026.109562

Machine learning-based short-term net load forecasting for residential buildings with integrated photovoltaic systems

2026-07-30

0

OA

AI

G

Georgios Tziolis *

A

Andreas Livera

J

Javier López-Lorente

P

Panagiotis Herodotou

G

George Makrides

G

George E. Georghiou

DOI：10.1016/j.egyr.2026.109562

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Abstract

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• Short-term net load forecasting (STNLF) for solar-integrated residential buildings. • Categorization of households using self-organizing map and mean shift clustering. • Development of a Bayesian neural network (BNN) model for direct STNLF. • Improved forecasting accuracy achieved by the BNN compared to the naïve model. .

Keywords:

Machine learning

Net load forecasting

Photovoltaic systems

Residential buildings

Machine learning-based short-term net load forecasting for residential buildings with integrated photovoltaic systems

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