A Spatio-Temporal Attention Model for Short-Term Load Forecasting of Urban Electric-Vehicle Charging Stations and an Empirical Study of Spatial-Modeling Effectiveness
ST-Attention, a lightweight and modular forecasting model that integrates temporal self-attention, spatial self-attention, an adjacency-matrix bias, and a residual prediction head is proposed, which forecasts hourly regional charging energy using the open UrbanEV benchmark dataset from September 2022 to February 2023.