5 papers
Probabilistic Multi-Regional Solar Power Forecasting with Any-Quantile Recurrent Neural Networks
Slawek Smyl, PaweÅ PeÅka, Grzegorz Dudek
The increasing penetration of photovoltaic (PV) generation introduces significant uncertainty into power system operation, necessitating forecasting approaches that extend beyond d…
HKAN: Hierarchical Kolmogorov-Arnold Network without Backpropagation
Grzegorz Dudek, Tomasz Rodak
This paper introduces the Hierarchical Kolmogorov-Arnold Network (HKAN), a novel network architecture that offers a competitive alternative to the recently proposed Kolmogorov-Arno…
Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting
Mateusz Kasprzyk, PaweÅ PeÅka, Boris N. Oreshkin +1
This paper presents an enhanced N-BEATS model, N-BEATS*, for improved mid-term electricity load forecasting (MTLF). Building on the strengths of the original N-BEATS architecture,…
Any-Quantile Probabilistic Forecasting of Short-Term Electricity Demand
Slawek Smyl, Boris N. Oreshkin, PaweÅ PeÅka +1
Power systems operate under uncertainty originating from multiple factors that are impossible to account for deterministically. Distributional forecasting is used to control and mi…
Stacking for Probabilistic Short-term Load Forecasting
Grzegorz Dudek
In this study, we delve into the realm of meta-learning to combine point base forecasts for probabilistic short-term electricity demand forecasting. Our approach encompasses the ut…