Short-Term Probability Density Function Forecasting of Industrial Loads Based on ConvLSTM-MDN

Short-Term Probability Density Function Forecasting of Industrial Loads Based on ConvLSTM-MDN

Load forecasting for industrial customers is essential for reliable operation decisions in the electric power industry. However, most of the load forecasting literature has been focused on deterministic load forecasting (DLF) without considering information on the uncertainty of industrial load. Thi...

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Bibliographic Details
Main Authors: Yuan Y. Wang, Ting Y. Wang, Xiao Q. Chen, Xiang J. Zeng, Jing J. Huang, Xia F. Tang
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-04-01
Series:Frontiers in Energy Research
Subjects:
load forecasting
probability density
convolutional long short-term memory
mixture density network
industrial customers
Online Access:https://www.frontiersin.org/articles/10.3389/fenrg.2022.891680/full

Internet

https://www.frontiersin.org/articles/10.3389/fenrg.2022.891680/full

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