Mapping High-Performance Regions in Battery Scheduling across Data Uncertainty, Battery Design, and Planning Horizons

ArXi:2604.15360v1 Announce Type: new This study presents a triadic analysis of energy storage operation under multi-stage model predictive control, investigating the interplay between data characteristics, forecast uncertainty, planning horizon, and battery c-rate. Synthetic datasets are generated to systematically explore variations in data profiles and uncertainty, enabling parametrization and the construction of relationships that map these characteristics to optimal horizon length.