Electric Vehicle Charging Load Forecasting: An Experimental Comparison of Machine Learning Methods

ArXi:2512.17257v2 Announce Type: replace With the growing popularity of electric vehicles as a means of addressing climate change, concerns have emerged regarding their impact on electric grid management. As a result, predicting EV charging demand has become a timely and important research problem. While substantial research has addressed energy load forecasting in transportation, relatively few studies systematically compare multiple forecasting methods across different temporal horizons and spatial aggregation levels in diverse urban settings.