A Deep Learning Based Hybrid Framework for Day-Ahead Electricity Price Forecasting

A Deep Learning Based Hybrid Framework for Day-Ahead Electricity Price Forecasting

With the deregulation of the electric energy industry, accurate electricity price forecasting (EPF) is increasingly significant to market participants' bidding strategies and uncertainty risk control. However, it remains a challenging task owing to the high volatility and complicated nonlineari...

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Bibliographic Details
Main Authors: Rongquan Zhang, Gangqiang Li, Zhengwei Ma
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Electricity market
day-ahead electricity price forecasting
feature preprocessing
deep learning
error compensation
probabilistic forecasting
Online Access:https://ieeexplore.ieee.org/document/9157856/

Internet

https://ieeexplore.ieee.org/document/9157856/

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