Short-term microgrid load probability density forecasting method based on k-means-deep learning quantile regression

Traditional short-term load forecasting (STLF) methods for large utility grid systems usually provide the forecasted load with deterministic points. However, deterministic load forecasting cannot reveal the load pattern and uncertainty of controllable load in a microgrid, where the prediction errors...

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Detalhes bibliográficos

Principais autores:	Zilong Zhao, Jinrui Tang, Jianchao Liu, Ganheng Ge, Binyu Xiong, Yang Li
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Elsevier 2022-08-01
coleção:	Energy Reports
Assuntos:	Short-term load forecasting Probability density Quantile regression Long short-term memory neural network Kernel density estimation Microgrid
Acesso em linha:	http://www.sciencedirect.com/science/article/pii/S2352484722006758
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