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

This study presents a triadic analysis of battery scheduling under multi-stage model predictive control, investigating the interplay between data characteristics, forecast uncertainty, planning horizon, and battery c-rate. It identifies an "effective horizon" for optimal look-ahead length, enabling reduced computational costs and providing practical guidance for industrial storage operations.