Probabilistic Forecasting of Electric Vehicle Charging in a Time-varying Hierarchical Infrastructure
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Abstract (arXiv)
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 with recent advances in conformal prediction with missing data. The conformal procedures considered produce valid prediction intervals at every node of the hierarchy and the algorithm CP-MNR-Nested successfully accounts for the time-varying hierarchical structure of the data.
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References · 16
- 2016Distribution-Free Predictive Inference For Regressioncited by 668
- 2021Adaptive Conformal Inference Under Distribution Shiftcited by 375
- 2025TabICL: A Tabular Foundation Model for In-Context Learning on Large Datacited by 289
- 2019Predictive inference with the jackknife+cited by 211
- 2025TabArena: A Living Benchmark for Machine Learning on Tabular Datacited by 176
- 2022Adaptive Conformal Predictions for Time Seriescited by 161
- 2019Nested conformal prediction and quantile out-of-bag ensemble methodscited by 89
- 2025fev-bench: A Realistic Benchmark for Time Series Forecastingcited by 64
- 2020Kaggle forecasting competitions: An overlooked learning opportunitycited by 56
- 2023Conformal Prediction with Missing Valuescited by 25
- 2020Online Hierarchical Forecasting for Power Consumption Datacited by 10
- 2023Adaptive Probabilistic Forecasting of Electricity (Net-)Loadcited by 9
4 more
- 2024Conformal Prediction for Hierarchical Datacited by 5
- 2024Predictive Uncertainty Quantification with Missing Covariatescited by 4
- 2024Coherent Hierarchical Probabilistic Forecasting of Electric Vehicle Charging Demandcited by 3
- 2024Multivariate Online Linear Regression for Hierarchical Forecastingcited by 1
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