A new parametric framework shows that higher forecast uncertainty consistently shortens the optimal planning horizon for battery energy arbitrage across different battery designs.
Regularization via mass transportation.Journal of Machine Learning Research, 20(103):1–68
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Mapping High-Performance Regions in Battery Scheduling across Data Uncertainty, Battery Design, and Planning Horizons
A new parametric framework shows that higher forecast uncertainty consistently shortens the optimal planning horizon for battery energy arbitrage across different battery designs.