Mapping High-Performance Regions in Battery Scheduling across Data Uncertainty, Battery Design, and Planning Horizons
This study presents a controlled parametric framework for analyzing energy storage planning under uncertainty in a multi-stage model predictive control setting. The framework enables a broad and systematic exploration through parametrized generation of synthetic datasets in the context of energy price arbitrage. It facilitates the study of the joint effects of battery characteristics, signal structure, forecast uncertainty, and planning horizon on revenue performance in energy storage optimization, which are rarely considered together. The analysis is driven by two objectives. First, it characterizes how these interacting factors influence operational revenue and its sensitivity to planni...
| Authors | Jaime de Miguel Rodriguez, Artjom Vargunin, Brigitta Robin Raudne et al. |
|---|---|
| Primary category | cs.LG |
| Published | 12 April 2026 |
| Last updated at source | 6 May 2026 |
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