Two-Stage Attention Over LSTM With Bayesian Optimization for Day-Ahead Solar Power Forecasting

Two-Stage Attention Over LSTM With Bayesian Optimization for Day-Ahead Solar Power Forecasting

The penetration of PVs into the power grid is increasing day by day, as they are more economical and environment-friendly. However, due to the intrinsic intermittency in solar radiation and other meteorological factors, the generated power from PVs is uncertain and unstable. Therefore, accurate fore...

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Bibliographic Details
Main Authors: Muhammad Aslam, Seung-Jae Lee, Sang-Hee Khang, Sugwon Hong
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Attention
Bayesian optimization
day-ahead forecasting
deep-learning
LSTM
solar power forecasting
Online Access:https://ieeexplore.ieee.org/document/9496627/

Internet

https://ieeexplore.ieee.org/document/9496627/

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