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

This arxiv paper presents a framework for optimizing energy storage operation under multi-stage model predictive control, investigating how data uncertainty, forecast horizons, and battery characteristics affect performance. The study identifies an "effective horizon" beyond which additional forecast information provides diminishing returns, enabling computational savings. Results provide practical guidance for industrial storage systems across different battery types and uncertainty levels.