most citedA comparative assessment of deep learning models for day-ahead load forecasting: Investigating key accuracy drivers

33 citations · 33 across the 1 of their papers we have counts for

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cs.LG2023★ 33 cited

A comparative assessment of deep learning models for day-ahead load forecasting: Investigating key accuracy drivers

Sotiris Pelekis, Ioannis-Konstantinos Seisopoulos, Evangelos Spiliotis +4

Short-term load forecasting (STLF) is vital for the effective and economic operation of power grids and energy markets. However, the non-linearity and non-stationarity of electrici…