A novel multi-step ahead solar power prediction scheme by deep learning on transformer structure-Reference-Cited by-同舟云学术

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A novel multi-step ahead solar power prediction scheme by deep learning on transformer structure

Published:2024-09 Issue: Volume:230 Page:120780
ISSN:0960-1481
Container-title:Renewable Energy
language:en
Short-container-title:Renewable Energy

Author:

Mo Fan,Jiao Xuan,Li Xingshuo^ORCID,Du Yang^ORCID,Yao Yunting,Meng Yuxiang,Ding Shuye

Publisher

Elsevier BV

Reference33 articles.

1. Photovoltaic power forecasting: A hybrid deep learning model incorporating transfer learning strategy;Tang;Renew. Sustain. Energy Rev.,2022

2. Two-stage hybrid deep learning with strong adaptability for detailed day-ahead photovoltaic power forecasting;Li;IEEE Trans. Sustain. Energy,2022

3. Accurate one step and multistep forecasting of very short-term PV power using LSTM-TCN model;Limouni;Renew. Energy,2023

4. An optimized offline random forests-based model for ultra-short-term prediction of PV characteristics;Ibrahim;IEEE Trans. Ind. Inform.,2019

5. Robust proactive power smoothing control of PV systems based on deep reinforcement learning;Chen;IEEE Trans. Sustain. Energy,2023

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