Price-Aware and Explainable Analytics for Urban Electric Vehicle
Charging Networks: Forecasting Utilization Regimes for Sustainable
Charging Operations
Heba Moselhy1,∗, Noura Metawa2
1Business Administration Department, Delta Higher Institute for Management and Accounting Information
Systems, Egypt
2College of Business Administration, University of Sharjah, UAE
Emails: hebamoselhy5299@std.mans.edu.eg; nmetawa@sharjah.ac.ae
Abstract
The efficient functioning of the electric-vehicle charging systems that are publicly operated has become focused
on reliable short-horizon forecasting. The paper establishes an explainable and price-conscious analytical
model to predict short-term charging usage and demonstrate the utility of tariff signals in an urban
charging system. The analysis is based on UrbanEV benchmark, a new six months hourly panel of Shenzhen
public charging infrastructure, which integrates occupancy, charging time, charging volume, electricity
tariffs, service charges, weather and spatial descriptors. The concept of charging occupancy is considered an
operation state variable with connection to queue exposure, reliability of service, and tactical intervention. A
succinct mathematical formulation is created to use it in one-step-ahead utilization forecasting and in interpreting
low-, medium-, and high-utilization regime. The empirical analysis is pegged to benchmark evidence
reported to UrbanEV, where transformer-based forecasting had the best node-level performance and TimeXer
had the best RMSE values of 0.07 in occupancy, 2.73 in charging duration, and 43.66 in charging volume.
Further discussion indicates that occupancy prediction is accurate enough to justify regime based intervention
and strongest additional gains are obtained through the joint effect of pricing variables and temperature-price
interactions as opposed to single covariates. The results justify the justifiable, price-conscious forecasting as
an operational decision tool to alleviate congestion, design tariffs and specific capacity planning in sustainable
charging networks.