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Attention mechanism based solar and load joint forecasting framework with Bayesian optimization
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DOI:10.1016/j.compeleceng.2026.111327.png)
Abstract
En 中文
• Analyzed cross/auto-correlation in solar-load data to reveal temporal links. • Proposed Bi-LSTM with attention for joint solar and load forecasting. • Used Bayesian optimization to tune hyperparameters for better accuracy. • Achieved higher prediction accuracy than benchmark forecasting models. • Enables improved energy management in renewable-integrated grids.
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4.9
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6.7K
Citations:
1.3W
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