paper
2019
Applications & impacts
New model or method
RNN / LSTM / ConvLSTM6 h–3 days Journal
2019-01-01
008
Jan 2019
Ümit Cali, Vinayak Sharma
International Journal of Smart Grid and Clean Energy
LSTM-RNN forecasts Sotavento wind farm power 1 to 24 hours ahead using NWP inputs chosen by sensitivity analysis.
Short-term wind power forecasting using long-short term memory based recurrent neural network model and variable selection
In one sentence. LSTM-RNN forecasts Sotavento wind farm power 1 to 24 hours ahead using NWP inputs chosen by sensitivity analysis.
Labels
- Topic
- Applications & impacts
- Type
- New model or method
- Method
- RNN / LSTM / ConvLSTM
- Time scale
- 6 h–3 days
- Domain
- Local / station
- Data
- NWP analysis or forecasts (IFS, GFS, ...), Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.12720/sgce.8.2.103-110 OpenAlex:W2959898713
- Added
- 2026-10-22
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