Analysis of the feasibility of deep learning models for subseasonal solar and wind forecasting based on time-series patterns

Oh, Myeongchan

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Abstract: Analysis of the feasibility of deep learning models for subseasonal solar and wind forecasting based on time-series patterns (AGU25)

Analysis of the feasibility of deep learning models for subseasonal solar and wind forecasting based on time-series patterns

Myeongchan Oh¹, Donggun Oh², Minkyu Lee² and Chang Ki Kim², (1)Korea Institute of Energy Research, Renewable Energy Big Data Laboratory, Deajeon, South Korea, (2)Korea Institute of Energy Research, Renewable Energy Big Data Laboratory, Daejeon, South Korea