Decision-calibrated prediction sets learned via partially input-convex neural networks and calibrated with conformal risk control achieve closer adherence to constraint-satisfaction targets in robust DC optimal power flow than coverage-based sets.
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Decision-calibrated prediction sets for robust power system operations
Decision-calibrated prediction sets learned via partially input-convex neural networks and calibrated with conformal risk control achieve closer adherence to constraint-satisfaction targets in robust DC optimal power flow than coverage-based sets.