Probabilistic Forecasting of Electric Vehicle Charging in a Time-varying Hierarchical Infrastructure
Uncertainty quantification for electric vehicle (EV) charging demand is essential to turn the increasing pressure of EV adoption on power systems into a source of flexibility. We study a large-scale dataset of public charging stations in Scotland, where demand exhibits a hierarchical structure, organized across multiple aggregation levels, from individual charging points to regional and national scales. The charging infrastructure is continuously evolving, with new stations deployed and existing ones occasionally removed, which calls for forecasting and uncertainty quantification methods tailored to this evolving structure. To address these challenges, we combine hierarchical forecasting ...
| Authors | Guillaume Principato, Yvenn Amara-Ouali, Yannig Goude et al. |
|---|---|
| Primary category | stat.AP |
| Published | 9 October 2026 |
| Last updated at source | 9 October 2026 |
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