paper
2023
Applications & impacts
Application study
RNN / LSTM / ConvLSTM6 h–3 days Journal
2023-08-22
008
Aug 2023
Ogeuk Kwon, Hyunpyo Hong, Hyunsik Jo et al.
The Transactions of The Korean Institute of Electrical Engineers
LSTM forecasts hourly floating PV output from KMA weather forecasts at two Korean sites, meeting the 5% error threshold.
Prediction of a Floating Photovoltaic Generation Utilizing KMA Weather Forecast
In one sentence. LSTM forecasts hourly floating PV output from KMA weather forecasts at two Korean sites, meeting the 5% error threshold.
Labels
- Topic
- Applications & impacts
- Type
- Application study
- 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:10.5370/kiee.2023.72.8.904 OpenAlex:W4386064579
- Added
- 2026-10-22
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