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Interpretable load forecasting via representation learning of geo-distributed meteorological factors

Meteorological factors (MF) are crucial in day-ahead system-level load forecasting as they significantly influence electricity consumption behaviors. Numerous studies have incorporated MF into load forecasting models to achieve higher accuracy. Selecting MF from a representative location or using av...

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Principais autores: Yangze Zhou, Guoxin Lin, Dayan Sun, Zhifeng Liang, Ning Zhang
Format: Artigo
Sprog:Inglês
Udgivet: Elsevier 2025-11-01
Serier:International Journal of Electrical Power & Energy Systems
Fag:
Load forecasting
Geo-distributed meteorological factors
Model interpretation
Shapley value
Extreme scenarios
Online adgang:http://www.sciencedirect.com/science/article/pii/S0142061525008312
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