47 citations · 80 across the 4 of their papers we have counts for
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cs.LG2023★ 2 cited
Transfer learning for day-ahead load forecasting: a case study on European national electricity demand time series
Alexandros-Menelaos Tzortzis, Sotiris Pelekis, Evangelos Spiliotis +3
Short-term load forecasting (STLF) is crucial for the daily operation of power grids. However, the non-linearity, non-stationarity, and randomness characterizing electricity demand…
cs.LG2023★ 22 cited
In Search of Deep Learning Architectures for Load Forecasting: A Comparative Analysis and the Impact of the Covid-19 Pandemic on Model Performance
Sotiris Pelekis, Evangelos Karakolis, Francisco Silva +5
In power grids, short-term load forecasting (STLF) is crucial as it contributes to the optimization of their reliability, emissions, and costs, while it enables the participation o…