Decision-focused learning trains an LSTM PV forecaster on battery optimization objectives and cuts average electricity costs 3.6% versus standard two-stage forecasting despite 19.9% RMSE versus 8.2%.
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SolarTformer applies self-attention transformers to solar power forecasting and claims to outperform prior models on clear and cloudy days by incorporating power-station metadata for better generalization.
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Decision-focused learning for optimal PV-Battery scheduling
Decision-focused learning trains an LSTM PV forecaster on battery optimization objectives and cuts average electricity costs 3.6% versus standard two-stage forecasting despite 19.9% RMSE versus 8.2%.
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SolarTformer: A Transformer Based Deep Learning Approach for Short Term Solar Power Forecasting
SolarTformer applies self-attention transformers to solar power forecasting and claims to outperform prior models on clear and cloudy days by incorporating power-station metadata for better generalization.