2023
A Robust and Scalable Stacked Ensemble for Day-Ahead Forecasting of Distribution Network Losses
Gunnar Grotmol, Eivind Hovdegård Furdal, Nisha Dalal, Are Løkken Ottesen, Ella-Lovise Hammervold Rørvik, Martin Mølnå +2
AAAI 2023technical
Accurate day-ahead nominations of grid losses in electrical distribution networks are important to reduce the societal cost of these losses. We present a modification of the CatBoost ensemble-based system for day-ahead grid loss prediction detailed in Dalal et al. (2020), making four main changes. B…