The paper proposes a CVaR-guided decision-focused learning framework with risk-triggered re-optimization that improves probabilistic load forecasting and two-stage robust microgrid operation while reducing online computation.
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An end-to-end learning framework for joint building-data-center integrated energy systems improves operational performance 7-9% over predict-then-optimize baselines and cuts total energy cost ~10% via waste-heat recovery.
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CVaR-Guided Decision-Focused Learning and Risk-Triggered Re-Optimization for Two-Stage Robust Microgrid Operation
The paper proposes a CVaR-guided decision-focused learning framework with risk-triggered re-optimization that improves probabilistic load forecasting and two-stage robust microgrid operation while reducing online computation.
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End-to-End Learning-based Operation of Integrated Energy Systems for Buildings and Data Centers
An end-to-end learning framework for joint building-data-center integrated energy systems improves operational performance 7-9% over predict-then-optimize baselines and cuts total energy cost ~10% via waste-heat recovery.