Quantile-transformed multi-attention residual framework (QT-MARF) for medium-term PV and wind power prediction

Deep learning based ensemble approach for probabilistic wind power forecasting

Huaizhi Wang, Gangqiang Li, Guibin Wang et al. · Applied Energy · 2016 · 741 citations

Computing, Computational Engineering, Meteorology +16

Accurate photovoltaic power forecasting models using deep LSTM-RNN

Mohamed Abdel‐Nasser, Karar Mahmoud · Neural Computing and Applications · 2017 · 740 citations

Engineering, Meteorology, Forecasting +11

Short-Term Load Forecasting With Deep Residual Networks

Kunjin Chen, Kunlong Chen, Qin Wang et al. · IEEE Transactions on Smart Grid · 2018 · 672 citations

Computing, Computer Science, Electrical Engineering +17

A day-ahead PV power forecasting method based on LSTM-RNN model and time correlation modification under partial daily pattern prediction framework

Fei Wang, Zhiming Xuan, Zhao Zhen et al. · Energy Conversion and Management · 2020 · 622 citations

Computing, Data Science, Forecasting +16

A hybrid deep learning model for short-term PV power forecasting

Pengtao Li, Kaile Zhou, Xinhui Lu et al. · Applied Energy · 2019 · 498 citations

Agriculture, Data Science, Forecasting +13