Short-Term Forecasting of Photovoltaic Power Generation Based on Feature Selection and Bias Compensation–LSTM Network

Short-Term Forecasting of Photovoltaic Power Generation Based on Feature Selection and Bias Compensation–LSTM Network

In this paper, a hybrid model that considers both accuracy and efficiency is proposed to predict photovoltaic (PV) power generation. To achieve this, improved forward feature selection is applied to obtain the optimal feature set, which aims to remove redundant information and obtain related feature...

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Bibliographic Details
Main Authors: Cai Tao, Junjie Lu, Jianxun Lang, Xiaosheng Peng, Kai Cheng, Shanxu Duan
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Energies
Subjects:
photovoltaic power generation
feature selection
bias compensation–long short-term memory network
prediction accuracy
training time
Online Access:https://www.mdpi.com/1996-1073/14/11/3086

Internet

https://www.mdpi.com/1996-1073/14/11/3086

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