most citedIn Search of Deep Learning Architectures for Load Forecasting: A Comparative Analysis and the Impact of the Covid-19 Pandemic on Model Performance

22 citations · 22 across the 1 of their papers we have counts for

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1 paper

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…